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(English) The study of the colonic volume has strong relevance in gastroenterology and contributes to the diagnosis and research of lowseverity diseases such as constipation, diarrhea, or Irritable Bowel Syndrome. In the context of these affections, the use of invasive techniques or ionizing imaging is not advisable, and the medical experts opted for Magnetic Resonance Imaging (MRI) acquired without contrast administration nor any form of patient preparation to avoid exogenous colon alteration. Specifically, two MRI modalities are of special interest: T2-weighted half-Fourier acquisition single-shot turbo spin echo sequence (T2-HASTE), which allows the segmentation of the colon lumen, and T1-weighted Fat-Sat (T1-FS), where fecal and gas contents can be distinguished. The colon analysis requires the segmentation of the colon both in T1-FS and T2-HASTE images, which is a cumbersome and timeconsuming process when performed manually. Moreover, manual segmentation involves a high degree of uncertainty in the colon boundaries delimitation, which leads to arbitrariness and poor measurement repeatability. This Ph.D. Thesis proposes an end-to-end quasi-automatic framework that comprises all the steps required to accurately segment the colon in T2-HASTE and T1-FS images, allowing the study of its morphology and the colonic content distribution. In order to ease the validation of the automated segmentation results, a tool for the synchronized T1-FS/T2-HASTE visualization has also been designed. T2-HASTE segmentation is organized as a three-stage pipeline. In the first stage, a custom tubularity filter is run to detect colon candidate areas. The specialists provide a list of points along the colon trajectory, which are combined with tubularity information to calculate an estimation of the colon medial path. In the second stage, the colon region of interest is delimited by applying custom segmentation algorithms to detect colon neighboring regions and the fat capsule containing, (Català) L'estudi del volum colònic és especialment rellevant per a la gastroenterologia i contribueix al diagnòstic i la recerca de malalties de caràcter lleu com poden ser el restrenyiment, la diarrea o la síndrome del còlon irritable. En el context d'aquestes afectacions, l'ús de tècniques invasives o ionitzants no està prou justificat i els equips mèdics han optat per l'ús d'imatges per ressonància magnètica (MRI) adquirides sense contrast ni cap altra forma de preparació, evitant així l'alteració de l'estat natural del còlon. Existeixen dues modalitats de MRI d'especial interès per a aquest propòsit: T2-weighted half-Fourier acquisition single-shot turbo spin echo sequence (T2-HASTE), que permet la segmentació del lumen del còlon, i la seqüència T1-weighted Fat-Sat (T1-FS), en la que es pot distingir el contingut fecal i el gas intestinal. L'anàlisi del còlon requereix la segmentació completa a les dues modalitats, T1-FS i T2-HASTE, el que comporta un procés manual summament lent i laboriós. Addicionalment, la segmentació manual duu associada un alt grau d'incertesa al voltant dels contorns del còlon, que es tradueix en arbitrarietat i una baixa repetitividad dels mesuraments. Aquesta tesi proposa un sistema automatitzat extrem a extrem, que inclou tots els passos necessaris per a aconseguir una segmentació de còlon precisa en imatges T2-HASTE i T1-FS, permetent l'estudi de la morfologia i la distribució dels continguts colònics. Per a facilitar la validació dels resultats de la segmentació automàtica, s'ha desenvolupat una eina per a la visualització sincronitzada de totes dues modalitats T1-FS/T2-HASTE. La segmentació d'imatges T2-HASTE és un procés constituït per tres fases. En la primera, s'utilitza un filtre de tubularidad especialitzat per a detectar àrees candidates. Els metges marquen uns punts de referència al llarg del còlon, que en combinació amb la informació de tubularidad permeten calcular una estimació de la línia medial del còlon. En una segona, (Español) El estudio del volumen colónico es especialmente relevante para la gastroenterología y contribuye al diagnóstico y a la investigación de enfermedades de carácter leve como pueden ser el estreñimiento, la diarrea o el síndrome del colon irritable. En el contexto de dichas afectaciones, el uso de técnicas invasivas o ionizantes no está suficientemente justificado y los equipos médicos han optado por el uso de imágenes por resonancia magnética (MRI) adquiridas sin contraste ni ninguna otra forma de preparación, evitando así la alteración del estado natural del colon. Existen dos modalidades de MRI de especial interés para este propósito: T2-weighted half-Fourier acquisition single-shot turbo spin echo sequence (T2-HASTE), que permite la segmentación del lumen del colon, y la secuencia T1-weighted Fat- Sat (T1-FS), en la que se pueden distinguir el contenido fecal y el gas intestinal. El análisis del colon requiere la segmentación completa en ambas modalidades, T1-FS y T2-HASTE, lo que conlleva un proceso manual sumamente lento y laborioso. Adicionalmente, la segmentación manual lleva sujeta un alto grado de incertidumbre alrededor de los contornos del colon, que se traduce en arbitrariedad y un bajo nivel de repetitividad de las mediciones. Esta tesis propone un sistema automatizado extremo a extremo, que incluye todos los pasos necesarios para conseguir una segmentación de colon precisa en imágenes T2-HASTE y T1-FS, permitiendo el estudio de la morfología y la distribución de los contenidos colónicos. Para facilitar la validación de los resultados de la segmentación automática, se ha desarrollado una herramienta para la visualización sincronizada de ambas modalidades T1-FS/T2-HASTE. La segmentación de imágenes T2-HASTE es un proceso constituido por tres fases. En la primera, se utiliza un filtro de tubularidad especializado para detectar áreas candidatas. Los médicos marcan unos puntos de referencia a lo largo del colon, que en combinación con la información, Postprint (published version)

The analysis of colonic contents is a valuable tool for the gastroenterologist and has multiple applications in clinical routine. When considering magnetic resonance imaging (MRI) modalities, T2 weighted images are capable of segmenting the colonic lumen, whereas fecal and gas contents can only be distinguished in T1 weighted images. In this paper, we present an end-to-end quasi-automatic framework that comprises all the steps needed to accurately segment the colon in T2 and T1 images and to extract colonic content and morphology data to provide the quantification of colonic content and morphology data. As a consequence, physicians have gained new insights into the effects of diets and the mechanisms of abdominal distension, Peer Reviewed, Postprint (published version)

Herb Voelcker and his research team laid the foundations of Solid Modelling, on which Computer-Aided Design is based. He founded the ambitious Production Automation Project, that included Constructive Solid Geometry (CSG) as the basic 3D geometric representation. CSG trees were compact and robust, saving a memory space that was scarce in those times. But the main computational problem was Boundary Evaluation: the process of converting CSG trees to Boundary Representations (BReps) with explicit faces, edges and vertices for manufacturing and visualization purposes. This paper presents some glimpses of the history and evolution of some ideas that started with Herb Voelcker. We briefly describe the path from “localization and boundary evaluation” to “localization and printing”, with many intermediate steps driven by hardware, software and new mathematical tools: voxel and volume representations, triangle meshes, and many others, observing also that in some applications, voxel models no longer require Boundary Evaluation. In this last case, we consider the current research challenges and discuss several avenues for further research., Project TIN2017-88515-C2-1-R funded by MCIN/AEI/10.13039/501100011033/FEDER‘‘A way to make Europe’’, Peer Reviewed, Postprint (published version)

In many application areas, it is useful to convert the discrete information stored in the nodes of a regular grid into a continuous boundary model. Isosurface extraction algorithms differ on how the discrete information in the grid is generated, on what information does the grid store and on the properties of the output surface. Recent algorithms offer different solutions for the disambiguation problem and for controlling the final topology. Based on a number of properties of the grid’s grey cells and of the reconstruction algorithms, a characterization of several surface extraction strategies is proposed. The classification presented shows the inherent limitations of the different algorithms concerning global topology control and reconstruction of local features like thin portions of the volume and almost non-manifold regions. These limitations can be observed and are illustrated with some practical examples. We review in light of this classification some of the relevant papers in the literature, and see that they cluster in some areas of the proposed hierarchy, making a case for where it might be more interesting to focus in future research., Preprint

Computerized Tomography (CT) and, more recently, Magnetic Resonance Imaging (MRI) have become the state-of-the art techniques for morpho-volumetric analysis of abdominal cavities. Due to its constant motility, the colon is an organ difficult to analyze. Unfortunately, CT’s radiative nature makes it only indicated for patients with important disorders. Lately, acquisition techniques that rely on the use of MRI have matured enough to enable the analysis of colon data. This allows gathering data of patients with- out preparation (i.e. administration of drugs or contrast agents), and incorporating data of patients with non life-threatening diseases and healthy subjects to databases. In this paper we present an end-to-end framework that comprises all the steps to extract colon content and morphology data coupled with a web-based visualization tool that facilitates the visual exploration of such data. We also introduce the set of tools for the extraction of morphological data, and a detailed description of a specifically-designed interactive tool that facilitates a visual comparison of numerical variables within a set of patients, as well as a detailed inspection of an individual. Our prototype was evaluated by domain experts, which showed that our visual approach may reduce the costly process of colon data analysis. As a result, physicians have been able to get new insights on the effects of diets, and also to obtain a better understanding on the motility of the colon., This project has been supported by the project TIN2017-88515-C2-1-R (GEN3DLIVE), from the Spanish Ministerio de Economía y Competitividad with FEDER (EU) funds., Peer Reviewed, Postprint (author's final draft)

The study of the colonic volume is a procedure with strong relevance to gastroenterologists. Depending on the clinical protocols, the volume analysis has to be performed on MRI of the unprepared colon without contrast administration. In such circumstances, existing measurement procedures are cumbersome and time-consuming for the specialists. The algorithm presented in this paper permits a quasi-automatic segmentation of the unprepared colon on T2-weighted MRI scans. The segmentation algorithm is organized as a three-stage pipeline. In the first stage, a custom tubularity filter is run to detect colon candidate areas. The specialists provide a list of points along the colon trajectory, which are combined with tubularity information to calculate an estimation of the colon medial path. In the second stage, we delimit the region of interest by applying custom segmentation algorithms to detect colon neighboring regions and the fat capsule containing abdominal organs. Finally, within the reduced search space, segmentation is performed via 3D graph-cuts in a three-stage multigrid approach. Our algorithm was tested on MRI abdominal scans, including different acquisition resolutions, and its results were compared to the colon ground truth segmentations provided by the specialists. The experiments proved the accuracy, efficiency, and usability of the algorithm, while the variability of the scan resolutions contributed to demonstrate the computational scalability of the multigrid architecture. The system is fully applicable to the colon measurement clinical routine, being a substantial step towards a fully automated segmentation., Postprint (author's final draft)

The analysis of the morphology and content of the gut is necessary in order to achieve a better understanding of its metabolic and functional activity. Magnetic resonance imaging (MRI) has become an important imaging technique since it is able to visualize soft tissues in an undisturbed bowel using no ionizing radiation. In the last few years, MRI of gastrointestinal function has advanced substantially. However, few studies have focused on the colon, because the analysis of colonic content is time consuming and cumbersome. This paper presents a semi-automatic segmentation tool for the quantitative assessment of the unprepared colon from MRI images. The techniques developed here have been crucial for a number of clinical experiments., Peer Reviewed, Postprint (published version)

The main goal for this master's degree final thesis is to propose an alternative way of computing solar radiation pressure. Solar radiation pressure is the impact of the photons emitted by the Sun onto a satellite. This impact generates acceleration that is important to model satellite's motion.

Background: Some patients complain that eating lettuce, gives them gas and abdominal distention. Our aim was to determine to what extent the patients' assertion is sustained by evidence. Methods: An in vitro study measured the amount of gas produced during the process of fermentation by a preparation of human colonic microbiota (n = 3) of predigested lettuce, as compared to beans, a high gas-releasing substrate, to meat, a low gas-releasing substrate, and to a nutrient-free negative control. A clinical study in patients complaining of abdominal distention after eating lettuce (n = 12) measured the amount of intestinal gas and the morphometric configuration of the abdominal cavity in abdominal CT scans during an episode of lettuce-induced distension as compared to basal conditions. Key Results: Gas production by microbiota fermentation of lettuce in vitro was similar to that of meat (P = .44), lower than that of beans (by 78 ± 15%; P < .001) and higher than with the nutrient-free control (by 25 ± 19%; P = .05). Patients complaining of abdominal distension after eating lettuce exhibited an increase in girth (35 ± 3 mm larger than basal; P < .001) without significant increase in colonic gas content (39 ± 4 mL increase; P = .071); abdominal distension was related to a descent of the diaphragm (by 7 ± 3 mm; P = .027) with redistribution of normal abdominal contents. Conclusion and Inferences: Lettuce is a low gas-releasing substrate for microbiota fermentation and lettuce-induced abdominal distension is produced by an uncoordinated activity of the abdominal walls. Correction of the somatic response might be more effective than the current dietary restriction strategy., Peer Reviewed, Postprint (published version)

About 50% of the patients consulting a gastroenterology clinic report symptoms without detectable cause. Clinical researchers are interested in analyzing the volumetric evolution of colon segments under the effect of different diets and diseases. These studies require noninvasive abdominal MRI scans without using any contrast agent. In this work, we propose a colon segmentation framework designed to support T2-weighted abdominal MRI scans obtained from an unprepared colon. The segmentation process is based on an efficient and accurate quasiautomatic approach that drastically reduces the specialist interaction and effort with respect other state-of-the-art solutions, while decreasing the overall segmentation cost. The algorithm relies on a novel probabilistic tubularity filter, the detection of the colon medial line, probabilistic information extracted from a training set and a final unsupervised clustering. Experimental results presented show the benefits of our approach for clinical use., Peer Reviewed, Postprint (author's final draft)

The recent advances in VR headsets, such as the Oculus Rift or HTC Vive, at affordable prices offering a high resolution display, has empowered the development of immersive VR applications. Unfortunately, the rendering engine and the interaction devices, are not specifically designed to deal with volumetric data. In this paper we propose an immersive VR system that uses some well-known acceleration algorithms to achieve real-time rendering of volumetric datasets in an immersive VR system. Moreover, we have incorporated different basic interaction techniques to facilitate the inspection of the volume dataset. The interaction has been designed to be as natural as possible in order to achieve the most comfortable, user-friendly virtual experience. We have conducted an informal user study to evaluate the user preferences. Our evaluation shows that our application is perceived usable, easy of learn and very effective in terms of the high level of immersion achieved., Peer Reviewed, Postprint (author's final draft)

Mobile devices have experienced an incredible market penetration in the last decade. Currently, medium to premium smartphones are relatively affordable devices. With the increase in screen size and resolution, together with the improvements in performance of mobile CPUs and GPUs, more tasks have become possible. In this paper we explore the rendering of medium to large volumetric models on mobile and low performance devices in general. To do so, we present a progressive ray casting method that is able to obtain interactive frame rates and high quality results for models that not long ago were only supported by desktop computers., Peer Reviewed, Postprint (author's final draft)

This thesis concerns the specific field of visualization of medical models using commodity and mobile devices. Mechanisms for medical imaging acquisition such as MRI, CT, and micro-CT scanners are continuously evolving, up to the point of obtaining volume datasets of large resolutions (> 512^3). As these datasets grow in resolution, its treatment and visualization become more and more expensive due to their computational requirements. For this reason, special techniques such as data pre-processing (filtering, construction of multi-resolution structures, etc.) and sophisticated algorithms have to be introduced in different points of the visualization pipeline to achieve the best visual quality without compromising performance times. The problem of managing big datasets comes from the fact that we have limited computational resources. Not long ago, the only physicians that were rendering volumes were radiologists. Nowadays, the outcome of diagnosis is the data itself, and medical doctors need to render them in commodity PCs (even patients may want to render the data, and the DVDs are commonly accompanied with a DICOM viewer software). Furthermore, with the increasing use of technology in daily clinical tasks, small devices such as mobile phones and tablets can fit the needs of medical doctors in some specific areas. Visualizing diagnosis images of patients becomes more challenging when it comes to using these devices instead of desktop computers, as they generally have more restrictive hardware specifications. The goal of this Ph.D. thesis is the real-time, quality visualization of medium to large medical volume datasets (resolutions >= 512^3 voxels) on mobile phones and commodity devices. To address this problem, we use multiresolution techniques that apply downsampling techniques on the full resolution datasets to produce coarser representations which are easier to handle. We have focused our efforts on the application of Volume Visualization in the clinical practic, Esta tesis se centra en la visualización de modelos médicos de volumen en dispositivos móviles y de bajas prestaciones. Los sistemas médicos de captación tales como escáners MRI, CT y micro-CT, están en constante evolución, hasta el punto de obtener modelos de volumen de gran resolución (> 512^3). A medida que estos datos crecen en resolución, su manejo y visualización se vuelve más y más costoso debido a sus requisitos computacionales. Por este motivo, técnicas especiales como el pre-proceso de datos (filtrado, construcción de estructuras multiresolución, etc.) y algoritmos específicos se tienen que introducir en diferentes puntos de la pipeline de visualización para conseguir la mejor calidad visual posible sin comprometer el rendimiento. El problema que supone manejar grandes volumenes de datos es debido a que tenemos recursos computacionales limitados. Hace no mucho, las únicas personas en el ámbito médico que visualizaban datos de volumen eran los radiólogos. Hoy en día, el resultado de la diagnosis son los datos en sí, y los médicos necesitan renderizar estos datos en PCs de características modestas (incluso los pacientes pueden querer visualizar estos datos, pues los DVDs con los resultados suelen venir acompañados de un visor de imágenes DICOM). Además, con el reciente aumento del uso de las tecnologías en la clínica práctica habitual, dispositivos pequeños como teléfonos móviles o tablets son los más convenientes en algunos casos. La visualización de volumen es más difícil en este tipo de dispositivos que en equipos de sobremesa, pues las limitaciones de su hardware son superiores. El objetivo de esta tesis doctoral es la visualización de calidad en tiempo real de modelos grandes de volumen (resoluciones >= 512^3 voxels) en teléfonos móviles y dispositivos de bajas prestaciones. Para enfrentarnos a este problema, utilizamos técnicas multiresolución que aplican técnicas de reducción de datos a los modelos en resolución original, para así obtener modelos de m, Postprint (published version)

L'objectiu principal d'aquest treball de fi de grau ha sigut estudiar la viabilitat d'entorns de realitat virtual immersius per inspeccionar models anatòmics de forma col·lectiva en un entorn anàleg al d'una classe., The main objective of this bachelor's thesis has been studying the viability of immersive virtual reality environments to examine anatomic models collectively in an environment analogous to that of a classroom.

Volume visualization software usually has to deal with datasets that are larger than the GPUs may hold. This is especially true in one of the most popular application scenarios: medical visualization. Typically, medical datasets are available for different personnel, but only radiologists have high-end systems that are able to cope with large data. For the rest of physicians, usually low-end systems are only available. As a result, most volume rendering packages downsample the data prior to uploading to the GPU. The most common approach consists in performing iterative subsampling along the longest axis, until the model fits inside the GPU memory. This causes important information loss that affects the final rendering. Some cleverer techniques may be developed to preserve the volumetric information. In this paper we explore the quality of different downsampling methods and present a new approach that produces smooth lower-resolution representations, yet still preserves small features that are prone to disappear with other approaches., Peer Reviewed, Postprint (published version)

The way in which gradients are computed in volume datasets influences both the quality of the shading and the performance obtained in rendering algorithms. In particular, the visualization of coarse datasets in multi-resolution representations is affected when gradients are evaluated on-the-fly in the shader code by accessing neighbouring positions. This is not only a costly computation that compromises the performance of the visualization process, but also one that provides gradients of low quality that do not resemble the originals as much as desired because of the new topology of downsampled datasets. An obvious solution is to pre-compute the gradients and store them. Unfortunately, this originates two problems: First, the downsampling process, that is also prone to generate artifacts. Second, the limited bit size of storage itself causes the gradients to loss precision. In order to solve these issues, we propose a downsampling filter for pre-computed gradients that provides improved gradients that better match the originals such that the aforementioned artifacts disappear. Secondly, to address the storage problem, we present a method for the efficient storage of gradient directions that is able to minimize the minimum angle achieved among all representable vectors in a space of 3 bytes. We also provide several examples that show the advantages of the proposed approaches., Peer Reviewed, Postprint (published version)

The analysis of the morphology and content of the gut is necessary in order to understand metabolic and functional gut activity and for diagnostic purposes. Magnetic resonance imaging (MRI) has become an important modality technique since it is able to visualize soft tissues using no ionizing radiation, and hence removes the need for any contrast agents. In the last few years, MRI of gastrointestinal function has advanced substantially, although scarcely any publication has been devoted to the analysis of the colon content. This paper presents a semi-automatic segmentation tool for the quantitative assessment of the unprepared colon from MRI images. This application has allowed for the analysis of the colon content in various clinical experiments. The results of the assessment have contributed to a better understanding of the functionality of the colon under different diet conditions. The last experiment carried out by medical doctors showed a marked influence of diet on colonic content, accounting for about 30% of the volume variations., Peer Reviewed, Postprint (published version)

L’objectiu global d’aquest projecte ha estat valorar la utilització d’un sistema immersiu de realitat virtual com l’HTC Vive per a la visualització i interacció de models volumètrics en aplicacions mèdiques. Per fer-ho, s’ha dissenyat i implementat un visualitzador basat en ray casting sobre la plataforma Unity 3D i s’ha optimitzat l’algorisme per obtenir-ne temps de renderitzat interactius. A més a més, s’han dissenyat i implementat tres metàfores d’interacció. Per últim, s’ha avaluat la usabilitat del sistema amb un test d’usuari que ha permès demostrar la viabilitat d’un sistema de visualització de models volumètrics en entorns de realitat virtual immersiva i identificar possibles millores per a l’aplicació desenvolupada., El objetivo global de este proyecto ha sido valorar la utilización de un sistema inmersivo de realidad virtual como el HTC Vive para la visualización e interacción de modelos volumétricos en aplicaciones médicas. Para ello, se ha diseñado e implementado un visualizador basado en ray casting sobre la plataforma Unity 3D y se ha optimizado el algoritmo para obtener tiempos de renderizado interactivos. Además, se han diseñado e implementado tres metáforas de interacción. Por último, se ha evaluado la usabilidad del sistema con un test de usuario que ha permitido demostrar la viabilidad de un sistema de visualización de modelos volumétricos en entornos de realidad virtual inmersiva e identificar posibles mejoras para la aplicación desarrollada., The overall objective of this project was to evaluate the use of an immersive virtual reality system like HTC Vive for the visualization and interaction of volumetric models in medical applications. To do this, we developed a rendering system based on ray casting and integrated into Unity3D. The algorithm has been optimized to obtain interactive rendering times. In addition, three interaction metaphors have been designed and implemented. Finally, we evaluated the usability of the system by doing a user test that proved the feasibility of a visualization system of volumetric models in immersive virtual reality environments and allowed us to identify possible improvements in the developed application.

This is the peer reviewed version of the following article: Bendezú, Á., Mego, M., Monclús, E., Merino, X., Accarino, A., Malagelada, J., Navazo, I., Azpiroz, F. Colonic content: effect of diet, meals, and defecation. "Neurogastroenterology and motility", Febrer 2017, vol. 29, núm. 2, which has been published in final form at [http://onlinelibrary.wiley.com.recursos.biblioteca.upc.edu/doi/10.1111/nmo.12930/full]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving., The metabolic activity of colonic microbiota is influenced by diet; however, the relationship between metabolism and colonic content is not known. Our aim was to determine the effect of meals, defecation, and diet on colonic content. Methods: In 10 healthy subjects, two abdominal MRI scans were acquired during fasting, 1 week apart, and after 3 days on low- and high-residue diets, respectively. With each diet, daily fecal output and the number of daytime anal gas evacuations were measured. On the first study day, a second scan was acquired 4 hours after a test meal (n=6) or after 4 hours with nil ingestion (n=4). On the second study day, a scan was also acquired after a spontaneous bowel movement. Results: On the low-residue diet, daily fecal volume averaged 145 ± 15 mL; subjects passed 10.6 ± 1.6 daytime anal gas evacuations and, by the third day, non-gaseous colonic content was 479 ± 36 mL. The high-residue diet increased the three parameters to 16.5 ± 2.9 anal gas evacuations, 223 ± 19 mL fecal output, and 616 ± 55 mL non-gaseous colonic content (P<.05 vs low-residue diet for all). On the low-residue diet, non-gaseous content in the right colon had increased by 41 ± 11 mL, 4 hours after the test meal, whereas no significant change was observed after 4-hour fast (-15 ± 8 mL; P=.006 vs fed). Defecation significantly reduced the non-gaseous content in distal colonic segments. Conclusion & inferences: Colonic content exhibits physiologic variations with an approximate 1/3 daily turnover produced by meals and defecation, superimposed over diet-related day-to-day variations., Peer Reviewed, Postprint (author's final draft)

Throughout the years, many shading techniques have been developed to improve the conveying of information in volume visualization. Some of these methods, usually referred to as realistic, are supposed to provide better cues for the understanding of volume data sets. While shading approaches are heavily exploited in traditional monoscopic setups, no previous study has analyzed the effect of these techniques in virtual reality. To further explore the influence of shading on the understanding of volume data in such environments, we carried out a user study in a desktop-based stereoscopic setup. The goals of the study were to investigate the impact of well-known shading approaches and the influence of real illumination on depth perception. Participants had to perform three different perceptual tasks when exposed to static visual stimuli. 45 participants took part in the study, giving us 1152 trials for each task. Results show that advanced shading techniques improve depth perception in stereoscopic volume visualization. As well, external lighting does not affect depth perception when these shading methods are applied. As a result, we derive some guidelines that may help the researchers when selecting illumination models for stereoscopic rendering., Peer Reviewed, Postprint (published version)

Although Virtual Reality (VR) environments have seen slower adoption rates than expected among the medical community, throughout the last years, several new techniques and devices (e.g. Oculus Rift) have been developed that might boost the popularity of VR. However, the use of 3D environments is not exempt of some shortcomings, such as the difficulties of adaption to 3D, that sometimes produces motion sickness, or the increase in effort the user has to undergo when interacting with a 3D system, as compared to using a simple mouse on a desktop. Our proposal is tailored to focus on the second problem. More concretely, we propose a magnification technique that is able to reduce the movements required to explore a concrete part of a volumetric dataset as compared to other zooming techniques. Our technique, builds the zooming result in the same virtual position of the initial interaction while still maintaining a contextual view on the region of interest and its surroundings. This way, the user reduces the amount of movements required to explore a model and efficiency is increased. An informal user study was carried out that confirmed our hypotheses., Peer Reviewed, Postprint (published version)

This is the peer reviewed version of the following article: Bendezú, R. A., Barba, E., Burri, E., Cisternas, D., Accarino, A., Quiroga, S., Monclus, E., Navazo, I., Malagelada, J.-R. and Azpiroz, F. (2016), Colonic content in health and its relation to functional gut symptoms. Neurogastroenterol. Motil., 28: 849–854, which has been published in final form at [doi:10.1111/nmo.12782]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving, Gut content may be determinant in the generation of digestive symptoms, particularly in patients with impaired gut function and hypersensitivity. Since the relation of intraluminal gas to symptoms is only partial, we hypothesized that non-gaseous component may play a decisive role. Methods: Abdominal computed tomography scans were evaluated in healthy subjects during fasting and after a meal (n = 15) and in patients with functional gut disorders during basal conditions (when they were feeling well) and during an episode of abdominal distension (n = 15). Colonic content and distribution were measured by an original analysis program. Key results: In healthy subjects both gaseous (87 ± 24 mL) and non-gaseous colonic content (714 ± 34 mL) were uniformly distributed along the colon. In the early postprandial period gas volume increased (by 46 ± 23 mL), but non-gaseous content did not, although a partial caudad displacement from the descending to the pelvic colon was observed. No differences in colonic content were detected between patients and healthy subjects. Symptoms were associated with discrete increments in gas volume. However, no consistent differences in non-gaseous content were detected in patients between asymptomatic periods and during episodes of abdominal distension. Conclusions & inferences: In patients with functional gut disorders, abdominal distension is not related to changes in non-gaseous colonic content. Hence, other factors, such as intestinal hypersensitivity and poor tolerance of small increases in luminal gas may be involved., Peer Reviewed, Postprint (author's final draft)

GPU for rendering accurate touch sensation in highly complex geometric models. An object’s geometry is covered completely by a connected mesh of edge-joined prismoids, while surface detail is encoded by an image-based approach in a special tangent space flat texture containing relief and surface normals values. Heights and normals within each prism are warped from object volume space to orthogonal tangent space, by means fast method for computing barycentric coordinates, and stored in a per-face sorted RGBA texture. Parallel computation is performed in GPU for many prisms at once. Applying a unified treatment of collision detection in conformal space from euclidean R3 (3D) to a higher dimensional conformal space R4;1 (5D), CUDA core kernels perform parallel real-time collision detection in GPU, with a haptic probe’s position vector without any bounding volume prefiltering, to identify which prisms of the object’s surface are being touched, and then map coordinates to tangent space, sampling relative surface height and normal from texture, for a final decision on whether the surface was hit. Results show throughput is increased between one and two orders of magnitude in collision benchmarks among known mesh models, computed in blind all vs. all manner, accurately colliding against 3D surface detail at high sampling rates without degrading touch sensation., Peer Reviewed, Postprint (published version)

The final publication is available at Springer via http://dx.doi.org/10.1007/s00371-016-1253-9, Medical datasets are continuously increasing in size. Although larger models may be available for certain research purposes, in the common clinical practice the models are usually of up to 512x512x2000 voxels. These resolutions exceed the capabilities of conventional GPUs, the ones usually found in the medical doctors’ desktop PCs. Commercial solutions typically reduce the data by downsampling the dataset iteratively until it fits the available target specifications. The data loss reduces the visualization quality and this is not commonly compensated with other actions that might alleviate its effects. In this paper, we propose adaptive transfer functions, an algorithm that improves the transfer function in downsampled multiresolution models so that the quality of renderings is highly improved. The technique is simple and lightweight, and it is suitable, not only to visualize huge models that would not fit in a GPU, but also to render not-so-large models in mobile GPUs, which are less capable than their desktop counterparts. Moreover, it can also be used to accelerate rendering frame rates using lower levels of the multiresolution hierarchy while still maintaining high-quality results in a focus and context approach. We also show an evaluation of these results based on perceptual metrics., Peer Reviewed, Postprint (author's final draft)

The final publication is available at Springer via http://dx.doi.org/10.1016/j.cad.2016.06.005, The use of virtual prototypes and digital models containing thousands of individual objects is commonplace in complex industrial applications like the cooperative design of huge ships. Designers are interested in selecting and editing specific sets of objects during the interactive inspection sessions. This is however not supported by standard visualization systems for huge models. In this paper we discuss in detail the concept of rendering front in multiresolution trees, their properties and the algorithms that construct the hierarchy and efficiently render it, applied to very complex CAD models, so that the model structure and the identities of objects are preserved. We also propose an algorithm for the interactive inspection of huge models which uses a rendering budget and supports selection of individual objects and sets of objects, displacement of the selected objects and real-time collision detection during these displacements. Our solution–based on the analysis of several existing view-dependent visualization schemes–uses a Hybrid Multiresolution Tree that mixes layers of exact geometry, simplified models and impostors, together with a time-critical, view-dependent algorithm and a Constrained Front. The algorithm has been successfully tested in real industrial environments; the models involved are presented and discussed in the paper., Peer Reviewed, Postprint (author's final draft)

There is an increasing interest on tele-medicine and tele-diagnostic solutions based on the remote inspection of volume data coming from multimodal imaging. Client-server architectures meet these functionalities. The use of mobile devices is sometimes required due to the portability and easy maintenance. However, transmission time for the volumetric information and low performance hardware properties, make quite complex the design of efficient visualization systems on these devices. In this paper, we present a hybrid approach which is based on regions of interest (ROIs) and on a transfer-function aware compression scheme. It has a good performance in terms of bandwidth requirements and storage needs in the client device, being flexible enough to represent several materials and volume structures in the ROI. Clients store a low-resolution version of the volume data and ROI-dependent high resolution segmented information. Data must be only sent whenever a new ROI is requested, but interaction in the client is autonomous - without any data transmission - while a certain ROI is inspected. A benchmark is presented to compare the proposed scheme with three existing approaches, on two different volume data models. The results show that our hybrid approach is compact, efficient and scalable, with compression rates that decrease when the size of the volume model increases., Peer Reviewed, Postprint (published version)

In the medical imaging field, interactive direct volume rendering of large volume datasets is a challenging task. Multi-resolution techniques deal with this problem by downsampling the original dataset to produce coarser representations. We present an evaluation of different downsampling filters with respect to their effectiveness at preserving details of the original dataset. Moreover, we propose a new Gaussian-based filter that produces quality lower-resolution representations and preserves small features that are prone to disappear., Peer Reviewed, Postprint (author's final draft)

A method for heat transfer that combines heat conduction and radiation. Our solution uses an explicit finite differences scheme for the heat conduction equation and a direct radiosity Monte Carlo technique to compute sun radiation. Then we generate a synthetic thermographic image.

Throughout the years, many shading techniques have been developed to improve the conveying of information in Volume Visualization. Some of these methods, usually referred to as realistic, are supposed to provide better cues for the understanding of volume data sets. While shading approaches are heavily exploited in traditional monoscopic setups, no previous study has analyzed the effect of these techniques in Virtual Reality. To further explore the influence of shading on the understanding of volume data in such environments, we carried out a user study in a desktop-based stereoscopic setup. The goals of the study were to investigate the impact of well-known shading approaches and the influence of real illumination on depth perception. Participants had to perform three different perceptual tasks when exposed to static visual stimuli. 45 participants took part in the study, giving us 1152 trials for each task. Results show that advanced shading techniques improve depth perception in stereoscopic volume visualization. As well, external lighting does not affect depth perception when these shading methods are applied. As a result, we derive some guidelines that may help the researchers when selecting illumination models for stereoscopic rendering., Peer Reviewed, Postprint (author's final draft)

BACKGROUND & AIMS: In patients with functional gut disorders, abdominal distension has been associated with descent of the diaphragm and protrusion of the anterior abdominal wall. We investigated mechanisms of abdominal distension in these patients. METHODS: We performed a prospective study of 45 patients (42 women, 24-71 years old) with functional intestinal disorders (27 with irritable bowel syndrome with constipation, 15 with functional bloating, and 3 with irritable bowel syndrome with alternating bowel habits) and discrete episodes of visible abdominal distension. Subjects were assessed by abdominothoracic computed tomography (n = 39) and electromyography (EMG) of the abdominothoracic wall (n = 32) during basal conditions (without abdominal distension) and during episodes of severe abdominal distension. Fifteen patients received a median of 2 sessions (range, 1-3 sessions) of EMG-guided, respiratory-targeted biofeedback treatment; 11 received 1 control session before treatment. RESULTS: Episodes of abdominal distension were associated with diaphragm contraction (19% +/- 3% increase in EMG score and 12 +/- 2 mm descent; P < .001 vs basal values) and intercostal contraction (14% +/- 3% increase in EMG scores and 6 +/- 1 mm increase in thoracic antero-posterior diameter; P < .001 vs basal values). They were also associated with increases in lung volume (501 +/- 93 mL; P < .001 vs basal value) and anterior abdominal wall protrusion (32 +/- 3 mm increase in girth; P < .001 vs basal). Biofeedback treatment, but not control sessions, reduced the activity of the intercostal muscles (by 19% +/- 2%) and the diaphragm (by 18% +/- 4%), activated the internal oblique muscles (by 52% +/- 13%), and reduced girth (by 25 +/- 3 mm) (P <= .009 vs pretreatment for all). CONCLUSIONS: In patients with functional gut disorders, abdominal distension is a behavioral response that involves activity of the abdominothoracic wall. This distension can be reduced with EMG-guided, respiratory, Peer Reviewed, Postprint (published version)

The present document exposes a different approach for haptic rendering, defined as the simulation of force interactions to reproduce the sensation of surface relief in dense models. Current research shows open issues in timely haptic interaction involving large meshes, with several problems affecting performance and fidelity, and without a dominant technique to treat these issues properly. Relying in pure geometric collisions when rendering highly dense mesh models (hundreds of thousands of triangles) sensibly degrades haptic rates due to the sheer number of collisions that must be tracked between the mesh's faces and a haptic probe. Several bottlenecks were identified in order to enhance haptic performance: software architecture and data structures, collision detection, and accurate rendering of surface relief. To account for overall software architecture and data structures, it was derived a complete component framework for transforming standalone VR applications into full-fledged multi-threaded Collaborative Virtual Reality Environments (CVREs), after characterizing existing implementations into a feature-rich superset. Enhancements include: a scalable arbitrated peer-to-peer topology for scene sharing; multi-threaded components for graphics rendering, user interaction and network communications; a collaborative user interface model for session handling; and interchangeable user roles with multi-camera perspectives, avatar awareness and shared annotations. We validate the framework by converting the existing ALICE VR Navigator into a complete CVRE, showing good performance in collaborative manipulation of complex models. To specifically address collision detection computation, we derive a conformal algebra treatment for collisions among points, segments, areas, and volumes, based on collision detection in conformal R{4,1} (5D) space, and implemented in GPU for faster parallel queries. Results show orders of magnitude time reductions in collisions computations, al, En aquesta tesi es presenta un novedós enfocament per a la percepció hàptica del relleu de models virtuals complexes mitjançant la simulació de les forces d'interacció entre la superfície i un element de contacte. La proposta contribueix a l'estat de l'art de la recerca en aquesta àrea incrementant l'eficiència i la fidelitat de la interacció hàptica amb grans malles de triangles. La detecció de col·lisions amb malles denses (centenars de milers de triangles) limita la velocitat de resposta hàptica degut al gran nombre d'avaluacions d'intersecció cara-dispositiu hàptic que s'han de realitzar. Es van identificar diferents alternatives per a incrementar el rendiment hàptic: arquitectures de software i estructures de dades específiques, algorismes de detecció de col·lisions i reproducció hàptica de relleu superficial. En aquesta tesi es presenten contribucions en alguns d'aquests aspectes. S'ha proposat una estructura completa de components per a transformar aplicacions de Realitat Virtual en Ambients Col·laboratius de Realitat Virtual (CRVEs) multithread en xarxa. L'arquitectura proposada inclou: una topologia escalable punt a punt per a compartir escenes; components multithread per a visualització gràfica, interacció amb usuaris i comunicació en xarxa; un model d'interfície d'usuari col·laboratiu per a la gestió de sessions; i rols intercanviables de l'usuari amb perspectives de múltiples càmeres, presència d'avatars i anotacions compartides. L'estructura s'ha validat convertint el navegador ALICE en un CVRE completament funcional, mostrant un bon rendiment en la manipulació col·laborativa de models complexes. Per a incrementar l'eficiència del càlcul de col·lisions, s'ha proposat un algorisme que treballa en un espai conforme R{4,1} (5D) que permet detectar col·lisions entre punts, segments, triangles i volums. Aquest algorisme s'ha implementat en GPU per obtenir una execució paral·lela més ràpida. Els resultats mostren reduccions en el temps de càlcul de col·lision, En esta tesis se presenta un enfoque novedoso para la percepción háptica del relieve de modelos virtuales complejos mediante la simulación de las fuerzas de interacción entre la superficie y un elemento de contacto. La propuesta contribuye al estado del arte de investigación en este área incrementando la eficiencia y fidelidad de interacción háptica con grandes mallas de triángulos. La detección de colisiones con mallas geométricas densas (cientos de miles de triángulos) limita la velocidad de respuesta háptica debido al elevado número de evaluaciones de intersección cara-dispositivo háptico que deben realizarse. Se identificaron diferentes alternativas para incrementar el rendimiento háptico: arquitecturas de software y estructuras de datos específicas, algoritmos de detección de colisiones y reproducción háptica de relieve superficial. En esta tesis se presentan contribuciones en algunos de estos aspectos. Se ha propuesto una estructura completa de componentes para transformar aplicaciones aisladas de Realidad Virtual en Ambientes Colaborativos de Realidad Virtual (CRVEs) multithread en red. La arquitectura propuesta incluye: una topología escalable punto a punto para compartir escenas; componentes multithread para visualización gráfica, interacción con usuarios y comunicación en red; un modelo de interfaz de usuario colaborativo para la gestión de sesiones; y roles intercambiables del usuario con perspectivas de múltiples cámaras, presencia de avatares y anotaciones compartidas. La estructura se ha validado convirtiendo el navegador ALICE en un CVRE completamente funcional, mostrando un buen rendimiento en la manipulación colaborativa de modelos complejos. Para incrementar la eficiencia del cálculo de colisiones, se ha propuesto un algoritmo que trabaja en un espacio conforme R4,1 (5D) que permite detectar colisiones entre puntos, segmentos, triángulos y volúmenes. Este algoritmo se ha implementado en GPU a efectos de obtener una ejecución paralelamás rápida. Los, Postprint (published version)

Background: The precise relation of intestinal gas to symptoms, particularly abdominal bloating and distension remains incompletely elucidated. Our aim was to define the normal values of intestinal gas volume and distribution and to identify abnormalities in relation to functional-type symptoms. Methods:Abdominal computed tomography scans were evaluated in healthy subjects (n = 37) and in patients in three conditions: basal (when they were feeling well; n = 88), during an episode of abdominal distension (n = 82) and after a challenge diet (n = 24). Intestinal gas content and distribution were measured by an original analysis program. Identification of patients outside the normal range was performed by machine learning techniques (one-class classifier). Results are expressed as median (IQR) or mean ± SE, as appropriate. Key Results: In healthy subjects the gut contained 95 (71, 141) mL gas distributed along the entire lumen. No differences were detected between patients studied under asymptomatic basal conditions and healthy subjects. However, either during a spontaneous bloating episode or once challenged with a flatulogenic diet, luminal gas was found to be increased and/or abnormally distributed in about one-fourth of the patients. These patients detected outside the normal range by the classifier exhibited a significantly greater number of abnormal features than those within the normal range (3.7 ± 0.4 vs 0.4 ± 0.1; p < 0.001). Conclusions & Inferences: The analysis of a large cohort of subjects using original techniques provides unique and heretofore unavailable information on the volume and distribution of intestinal gas in normal conditions and in relation to functional gastrointestinal symptoms., Peer Reviewed, Postprint (author's final draft)

El objetivo global de este proyecto, es crear un editor de WebApps cómodo, eficiente y completo que permita a los desarrolladores abstraerse de las diversidad de plataformas, de las APIs gráficas y de la interacción cliente/servidor, para poder centrarse en desarrollar sus productos y servicios.

Medical doctors are often faced with the problem of selecting anchoring points in 3D space. These points are commonly used for measurement tasks, such as lengths of bones, or dimensions of pathological structures (e.g. tumours). Since previous research indicates that measurement tasks can be usually carried out more efficiently in VR environments than in desktop-based systems, we have concentrated on the development of selection tools for medical models. These models have a set of particularities such as the presence of semi-transparencies, and there is a lack of tools for measurement support for such models in VR environments. Our VR-based interaction technique uses the data to automatically generate candidate anchor points, and it is specially focused on the efficient selection of 3D points in datasets rendered using methods with semi-transparency such as Direct Volume Rendering. We will show that our method is effective, precise, and reduces the time and amount of movements required to set the anchor points as compared with other classical techniques based on clipping planes. We also provide a couple of improvements tailored to reduce the inherent imprecision of 3D devices due to hand vibration, and the flexibility in transfer function selection for anchor point definition., Peer Reviewed, Postprint (author’s final draft)

Peer Reviewed, Postprint (published version)

With current medical imaging improvements, specialists are being able to obtain correct information of anatomical structures of the human organism. By using different image visualization techniques, experts can obtain suitable images for bones, soft tissues, bloodstream among others. Present algorithms generate images with better and better resolution and information accuracy. Medical doctors are being more familiarized with three-dimensional structures reconstructed from bi-dimensional images. As a result, hospitals are becoming interested in tele-medicine and tele-diagnostic solutions. Client-server applications allow these functionalities. Sometimes the use of mobile devices is necessary due to their portability and easy maintenance. However, transmission time for the volumetric information and low performance hardware properties make quite complex the design of efficient visualization systems on these devices. The main objective of this thesis is to enrich user experience during the interactive visualization of volumetric medical models in low performance devices. To achieve this, a new transfer-function aware compression/decompression mechanism adapted to transmission, reconstruction and visualization has been studied. This work proposes several schemes to exploit the use of transfer functions (TFs) to enhance volume compression during data transmission to mobile devices. As far as we know, this possibility has not been considered by any of the described approaches in the previous work. The Wavelet-Based Volume Compression for Remote Visualization approach is a TF-aware compression scheme. It supports inspection of complex volume models with maximum level of detail in selected regions of interest (ROIs). It uses a GPU-based, ROI-aware ray-casting rendering algorithm in the client, with a limited amount of information being sent over the Network, decreasing storage size in the client side. Regarding the Remote Exploration of Volume Models using Gradient Octrees, Los adelantos actuales en imagenes médicas están permitiendo a los especialistas obtener información cada vez más precisa de las estructuras anatómicas del organismo humano. Mediante la utilización de diferentes técnicas de visualización, los expertos pueden obtener imágenes de calidad para los huesos, tejidos blandos y torrente sanguíneo, entre otros. Los actuales algoritmos de procesamiento de imágenes garantizan el equilibrio entre la resolución y la exactitud de la información. Paralelamente, los médicos están más familiarizados con las estructuras tridimensionales reconstruidas a partir de imágenes en dos dimensiones. Por otro lado, los hospitales están incorporando la tele-medicina y el tele-diagnóstico entre sus soluciones técnicas. Las aplicaciones cliente-servidor permiten estas funcionalidades. En ocasiones el uso de dispositivos móviles es necesario debido a su fácil mantenimiento y a su portabilidad. Sin embargo, el tiempo de transmisión de la información volumétrica así como el bajo rendimiento del hardware en estos dispositivos, hacen que el diseño de sistemas eficientes de visualización sea todavía una tarea compleja. El objetivo principal de esta tesis es enriquecer la experiencia del usuario en la visualización interactiva de modelos volumétricos de medicina en dispositivos de bajo rendimiento. Para conseguir esto, se ha puesto en práctica la implementación de un mecanismo de compresión/descompresión que depende de funciones de transferencia para optimizar la transmisión, reconstrucción y la visualización en estos dispositivos. Esta tesis, por lo tanto, propone varios esquemas para aprovechar el uso de las funciones de transferencia (TFs) e incrementar el ratio de compresión del volumen durante la transmisión a los dispositivos móviles. De acuerdo con nuestros conocimientos, ninguna de las técnicas descritas en los trabajos presentados anteriormente ha considerado esta posibilidad. El esquema de compresión de volumen basado en Wavelets para la visua, Postprint (published version)

Advances in Medical Visualization allows the analysis of anatomical structures with the use of 3D models reconstructed from a stack of intensity-based images acquired through different techniques, being Computerized Tomographic (CT) modality one of the most common. A general medical volume graphics application usually includes an exploration task which is sometimes preceded by an analysis process where the anatomical structures of interest are first identified. The main objective of this thesis is the improvement of the user experience in the analysis and exploration of medical datasets. This improvement involves the development of efficient algorithms designed both under a user-centered perspective and taking the new computing capabilities into account in order to obtain high quality results in real-time. On the analysis stage, we have focused on the identification of the bones at joints, which is particularly challenging because the bones are very close to each other and their boundaries become ambiguous in CT images. We have concentrated our efforts on reaching maximum automation of the overall process. The proposed algorithm uses an example mesh of the same bone that has to be segmented, usually from a different person, to drive the segmentation process. The algorithm is based on an energy minimization scheme to deform the initial example mesh while following the well-defined features of the volume data to be segmented in a local and adaptive way. We also present contributions on three different aspects of the exploration task: a best-view determination system and centering in virtual reality environments, a focus-and-context technique and a point selection method. In medical practice it would often be very useful to have access to a quick pre-visualization of the involved medical dataset. We have proposed a new system which allows users to obtain a set of representative views in a short time and permits the generation of inspection paths at almost no extra cost, Els avenços en la investigació en el camp de Medical Visualization permeten l’anàlisi de models volumètrics tridimensionals d’estructures anatòmiques obtinguts a partir d’imatgesmèdiques capturades mitjançant diferents tècniques, essent la Tomografia Computeritzada (TC) una de lesmés habituals. Generalment, les aplicacions informàtiques d’ajuda al diagnòstic, la simulació, etc., permeten l’exploració interactiva d’aquest tipus de models, una tasca que pot anar precedida d’un procés d’identificació (segmentació) de les estructures anatòmiques per tal de possibilitar la seva exploració. L’objectiu d’aquesta tesi és millorar l’eficiència i l’experiència de l’usuari, tant de la tasca de segmentació com de l’exploració. Per tal d’assolir-ho s’han desenvolupat diversos algorismes; dissenyats sota una perspectiva centrada en l’usuari i fent servir els darrers avenços tecnològics de las targes gràfiques, el que ens permet obtenir resultats visuals de màxima qualitat en temps real. Respecte de la tasca de segmentació, ens hem centrat en el problema de la identificació d’ossos ubicats en articulacions, en models capturats mitjançant TC. La identificació d’aquests ossos pot arribar a ser molt feixuga i costosa fent servir les tècniques clàssiques de segmentació. La recerca realitzada en elmarc de la tesi s’ha enfocat en assolir la màxima automatització possible del procés sencer. La tècnica proposada empra una malla triangular d’exemple de l’os que es vol segmentar, que es fará servir per guiar tot el procés de segmentació. L’algorisme deforma de forma local i adaptativa aquesta malla, adaptant-la a la informació present en el model volumètric en les parts en que la seva frontera està definida de forma no ambigua, i respectant la forma original en les zones en les que el model presenta algun tipus d’incertesa en la definició de la frontera, ja sigui be perque l’estructura òssia apareix totalment unida a altres estructures òssies de l’articulació o be degut a que la informació, Los avances en la investigación en el área de Medical Visualization permiten el análisis de modelos volumétricos tridimensionales de estructuras anatómicas, los cuales se obtienen a partir de imágenes médicas capturadas mediante diferentes técnicas de captación, siendo la Tomografía Computerizada (TC) una de las más frecuentes. Habitualmente, las aplicaciones informáticas orientadas al análisis de este tipo de modelos, bien sean para el soporte al diagnóstico, simuladores médicos o la planificación de procesos quirúrgicos, permiten la exploración interactiva de los modelos volumétricos. Dependiendo de las estructuras anatómicas que se precise analizar, puede ser necesario realizar un proceso de identificación (segmentación) de las estructuras anatómicas para posibilitar su posterior inspección. El objetivo principal de esta tesis ha consistido en el desarrollo de nuevas técnicas informáticas que mejoren la experiencia del usuario en los procesos tanto de segmentación como de exploración de un modelo volumétrico. Para alcanzar dicho objetivo, ha sido necesario el desarrollo de algoritmos eficientes diseñados teniendo particularmente en cuenta al usuario final y explotando los últimos avances en la tecnología de las tarjetas gráficas para poder obtener resultados visuales de la máxima calidad en tiempo real. En lo relativo al proceso de segmentación, nos hemos centrado en la identificación de las estructuras óseas ubicadas en articulaciones, en modelos capturadosmediante TC. La identificación de este tipo de estructuras usando los métodos tradicionales de segmentación puede llegar a ser muy tediosa, debido a que puede necesitarse mucha intervención por parte del usuario. La investigación llevada a cabo ha tenido como objetivo principal el maximizar el grado de automatización en el proceso de segmentación de este tipo de estructuras. La técnica propuesta parte de un ejemplo de la estructura ósea (malla triangular) que se quiere segmentar, generada a partir de los datos, Postprint (published version)