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This study proposes a virtual reconstruction method for fuzzy 3D images based on visual communication effects to improve recognition ability. This method includes constructing a grid distribution model for 3D images, recombining spatial information features using visual feature extraction, and detecting edges using contour feature extraction. A three-dimensional image visual communication model was established, and adaptive pixel reconstruction was achieved through fuzzy structure reconstruction method. Reconstruct the texture structure and grayscale histogram of 3D images to achieve high-quality virtual reconstruction. The simulation results verified the effectiveness of the method, and the designed simulation platform verified the accuracy and completeness of the method, demonstrating the improvement of existing systems and the potential for advancing the field of visual communication.

ABSTRACT: Objective: This in vitro study aimed to investigate enamel wear against 3 monolithic ceramics using 2 methods of measurement. Methods: Three groups of standard flat monolithic ceramic specimens including zirconia-reinforced lithium silicate glass (Vita Suprinity, VITA Zahnfabrik), yttria-stabilised tetragonal zirconia (Lava Esthetic Zirconia), and lithium disilicate glass (IPS e.max Press, Ivoclar Vivadent) were prepared, with human enamel used as the control group. Each specimen was subjected to the 2-body wear test at 49 N for 250,000 cycles. Enamel antagonists were evaluated with micro-computed tomography (CT) and intra-oral scanner, allowing 3-dimensional images of vertical wear and volumetric loss of enamel antagonists to be calculated. One-way analysis of variance followed by Student–Newman–Keuls post hoc tests were used to examine the differences in vertical wear/volumetric loss amongst the groups. Paired t tests and intra-class correlations were used to compare vertical wear/volumetric loss between the micro-CT and intra-oral scanner groups. Results: No significant difference in vertical wear was found amongst all groups. More volumetric loss was found in all test groups than in the control group (P < .001), but no significant difference was found amongst the test groups. There was a moderate positive correlation (r = 0.535, P = .033) between the vertical wear and volumetric loss. No significant difference between the 2 methods of measurement was found. Conclusions: Monolithic ceramics induce more enamel wear than natural teeth. Both micro-CT and intra-oral scanners can be used for measuring tooth wear with similar performance.

Pavement texture and skid resistance are pivotal surface features of roadway to traffic safety, especially under wet weather. Engineering interventions should be scheduled periodically to restore these features as they deteriorate over time under traffic polishing. While many studies have investigated the effects of traffic polishing on pavement texture and skid resistance through laboratory experiments, the absence of real-world traffic and environmental factors in these studies may limit the generalization of their findings. This study addresses this research gap by conducting a comprehensive field study of pavement texture and skid resistance under traffic polishing in the real world. A total of thirty pairs of pavement texture and friction data were systematically collected from three distinct locations with different levels of traffic polishing (middle, right wheel path, and edge) along an asphalt pavement in Oklahoma, USA. Data acquisition utilized a laser imaging device to reconstruct 0.01 mm 3D images to characterize pavement texture and a Dynamic Friction Tester to evaluate pavement friction at different speeds. Twenty 3D areal parameters were calculated on whole images, macrotexture images, and microtexture images to investigate the effects of traffic polishing on pavement texture from different perspectives. Then, texture parameters and testing speeds were combined to develop friction prediction models via linear and nonlinear methodologies. The results indicate that Random Forest models with identified inputs achieved excellent performance for non-contact friction evaluation. Last, the friction decrease rate was discussed to estimate the timing of future maintenance to restore skid resistance. This study provides more insights into how engineers should plan maintenance to restore pavement texture and friction considering real-world traffic polishing.

Three-dimensional technology using personal data records has been explored for human identification. The present study aimed to explore two methodologies, photography and orofacial scanning, for assessing orofacial records in forensic scenarios, highlighting their impact on human identification. A pilot and quasi-experimental study was performed using Canon 5D-Full Frame equipment (Tokyo, Japan) and an i700 scanner (Medit, Lusobionic, Portugal) (Seoul, Republic of Korea) with Medit Scan for Clinics (MSC) and Smile Design software (V3.3.2). The sample included living patients (n = 10) and individuals in forensic cases (n = 10). The study was divided into two complementary phases: (i) data collection using 2D and 3D technologies and (ii) visual comparison by superimposition procedures, 3D dental images with 3D facial records (3D–3D), and 2D photography with screen printing of 3D facial records (2D-3S). Statistical analyses were performed using descriptive procedures (Likert scale) and the Mann–Whitney U test. The Mann–Whitney U test comparing the data (n = 220 records) from living individuals and those in forensic cases identified statistically significant differences in the performance of the photographic methods for evaluating intraoral mineralisation (p = 0.004), intraoral soft tissues (p = 0.016), intraoral distortion (p = 0.005) and the scan methods for intraoral extra devices (p = 0.003) and extraoral soft tissues (p = 0.005). A visual comparison (n = 40) allowed 3D–3D superimposition. Additionally, 2D-3S superimposition qualitatively identified the middle third of the face as the corporal area within the anatomical features required for successful surgery. In conclusion, the present study presented evidence-based data suggesting that the IO scan method, as an emergent technology, should be explored as a valuable tool in forensic facial identification in real-world scenarios.

Vascular brain damage can manifest as various ophthalmic pathologies. It is important to understand cerebral circulation to understand the aetiopathogenesis of the disease. It can manifest as various ocular pathologies with visual field defects, cranial nerve palsies, orbital diseases, etc. In this review, with the help of three-dimensional (3D) images, various ophthalmology-related cerebrovascular diseases, their diagnostic methods and their treatment modalities are explained in detail for neophytes.

Accurate geometric modeling of blood vessel lumen from 3D images is crucial for vessel quantification as part of the diagnosis, treatment, and monitoring of vascular diseases. Our method, unlike other approaches which assume a circular or elliptical vessel cross-section, employs parametric B-splines combined with image formation system equations to accurately localize the highly curved lumen boundaries. This approach avoids the need for image segmentation, which may reduce the localization accuracy due to spatial discretization. We demonstrate that the model parameters can be reliably identified by a feedforward neural network which, driven by the cross-section images, predicts the parameter values many times faster than a reference least-squares (LS) model fitting algorithm. We present and discuss two example applications, modeling the lower extremities of artery–vein complexes visualized in steady-state contrast-enhanced magnetic resonance images (MRI) and the coronary arteries pictured in computed tomography angiograms (CTA). Beyond applications in medical diagnosis, blood-flow simulation and vessel-phantom design, the method can serve as a tool for automated annotation of image datasets to train machine-learning algorithms.

Introduction: The use of automation and sensor-based systems in livestock production allows monitoring of individual cows in real-time and provides the possibility of early warning systems to take necessary management actions against possible anomalies. Among the different RT monitoring parameters, body weight (BW) plays an important role in tracking the productivity and health status.Methods: In this study, various supervised learning techniques representing different families of methods in the machine learning space were implemented and compared for performance in the prediction of body weight from 3D image data in dairy cows. A total of 83,011 records of contour data from 3D images and body weight measurements taken from a total of 914 Danish Holstein and Jersey cows from 3 different herds were used for the predictions. Various metrics including Pearson’s correlation coefficient (r), the root mean squared error (RMSE), and the mean absolute percentage error (MAPE) were used for robust evaluation of the various supervised techniques and to facilitate comparison with other studies. Prediction was undertaken separately within each breed and subsequently in a combined multi-breed dataset.Results and discussion: Despite differences in predictive performance across the different supervised learning techniques and datasets (breeds), our results indicate reasonable prediction accuracies with mean correlation coefficient (r) as high as 0.94 and MAPE and RMSE as low as 4.0 % and 33.0 (kg), respectively. In comparison to the within-breed analyses (Jersey, Holstein), prediction using the combined multi-breed data set resulted in higher predictive performance in terms of high correlation coefficient and low MAPE. Additional tests showed that the improvement in predictive performance is mainly due to increase in data size from combining data rather than the multi-breed nature of the combined data. Of the different supervised learning techniques implemented, the tree-based group of supervised learning techniques (Catboost, AdaBoost, random forest) resulted in the highest prediction performance in all the metrics used to evaluate technique performance. Reported prediction errors in our study (RMSE and MAPE) are one of the lowest in the literature for prediction of BW using image data in dairy cattle, highlighting the promising predictive value of contour data from 3D images for BW in dairy cows under commercial farm conditions.

Aim: Cleft lip and palate (CLP) patients have a greater predisposition to tooth malformation, which could affect pulp volume. The aim of this study is to evaluate the dental pulp volume of central incisors in 3D images between individuals with and without CLP. Materials and Methods: This retrospective case-control study is single-centered and was recruited between January 2016 and October 2022. Ninety-four patients who were followed in the Institute of Orthodontics were evaluated and divided into two groups: a control group of patients without CLP and a test group of patients with CLP. The 3D data were imported by 3D image semi-automatic segmenting software named ITK-SNAP to calculate tooth pulp volume. Results: The dental pulp volume for both groups, control and CLP, did not show statistically significant differences. In the cleft group, when comparing the pulp volume between the cleft side and the non-cleft side, the cleft side showed a smaller volume. Regarding age and sex, no statistically significant differences were observed. Conclusions: Although there are no differences in mean pulp volume between patients with and without CLP, there is a pulp volume reduction in the teeth on the cleft side when compared to the unaffected contralateral side.

In this paper, a novel 3D image encryption based on the memristive chaotic system and RNA crossover and mutation is proposed. Firstly, the dynamic characteristics of the nonlinear system with two memristors are analyzed, including phase diagrams, Lyapunov exponential spectrums, and bifurcation diagrams. According to the merged image of three 3D images, the initial values of the memristive chaotic system are generated by SHA-256. Then the vertex coordinates are scrambled and diffused by 3D Arnold matrix and chaotic sequences. Finally, according to the dynamical encoding and decoding rules, crossover and RNA mutation are designed to confuse and diffuse the vertex coordinates. Throughout the encryption process, the Arnold matrix, RNA encoding and decoding rules, and crossover and mutation algorithms are determined by the memristive chaotic system. The experimental results verify that the proposed cryptosystem could encrypt three 3D images at the same time and resist various attacks effectively, and has good security performance.

Abstract Background The volumetric ratio of the tongue to the oral cavity has been recognized to be one of the important factors for the maintenance of stable occlusion. Oral cavity capacity is changed after orthognathic surgery in patients with mandibular prognathism; however, the volumetric changes of the oral cavity including the tongue before and after surgery have not been analyzed. The purpose of this study was to evaluate the morphological and volumetric changes of the tongue and oral cavity following orthognathic surgery using a newly developed vinyl polysiloxane impression method. Materials and methods The study was performed in fifteen subjects who underwent surgical orthognathic treatment. Impressions of the tongue together with the oral cavity were obtained before orthognathic surgery and 1, 3, and 6 months after orthognathic surgery. These impression patterns were scanned using cone-beam computed tomography (CT), and three-dimensional (3D) images of the oral cavity including the tongue, and the upper and lower dental arches were reconstructed. The morphological and volumetric changes in the oral cavity capacity and the tongue volume were examined. Results The volume of the tongue with the volume of the oral cavity decreased after orthognathic surgery. There was a correlation between the decrease in the oral cavity capacity and tongue volume. The volumetric ratio of the tongue to the oral cavity seems to be maintained before and after orthognathic surgery. Conclusion VPS method, free from radiation exposure, may be useful for investigating the morphological and volumetric changes of the tongue and oral cavity, which may possibly influence the stability of the dental arch and occlusion during surgical orthodontic treatment.

In order to ensure the rationality of landscape design, it is of great practical significance to simulate the planning effect. Aiming at the problems of traditional garden landscape distribution simulation technology, this paper designs a new garden landscape distribution rationality simulation technology based on three-dimensional image and virtual reality technology. Firstly, a rational analysis method for landscape garden distribution based on three-dimensional images is proposed. Based on the correlation between different coordinate systems under a specific angle of view, a camera pose matrix is constructed, and SURF feature point detection is performed on the landscape garden image and the above feature points are clustered and matched. Secondly, the three-dimensional image reconstruction of the landscape garden image is realized based on the registered image feature points. Based on the three-dimensional image reconstruction results and virtual reality technology, the three-dimensional image analysis of the rationality of landscape distribution is completed. Finally, the case analysis and performance test results illustrate the superiority of the realized landscape garden distribution rationality technology. This method can provide scientific reference and basis for the modern landscape gardening industry to adopt three-dimensional images and other technologies.

BackgroundThe surgical separation of two Conjoined Twins is a particularly complex operation. Surgical times are particularly long and post-operative complications are very frequent in this type of procedure. We report a clinical case of surgical separation of two thoraco-omphalopagus conjoined twins in which, thanks to the use of (3D) three dimensional technologies, we were able to significantly reduce operative times and improve clinical outcomes.MethodsWe performed a 3D reconstruction of the anatomical parts involved in congenital fusion using Computer Tomography (CT) images.We obtained virtual anatomical models of the patients which allowed us to estimate essential details as the residual post-operative thoracic volume as well as the exact position of resection planes for both the general separation and for the hepatic splitting procedure. Subsequently, we printed 3D anatomical models of the thoracic cage and sternum and of the liver with the plane of resection. Finally, we printed an additional 3D anatomical model of the two patients representing different organs with multiple colors and materials.ResultsThe use of 3D printing reduced the duration of surgery by 30% with a favorable patient outcome. Two years after the operation, the patients do not present any type of deficit and have a normal life without any significant complication.ConclusionVirtual anatomical 3D models and 3D printing represent a valid technological tool to support complex surgical operations, especially in pre-surgical planning. 3D models are important tools to better understand complex anatomy and to discuss clinical cases among members of the surgical team.

Most commercially successful face recognition systems combine information from multiple sensors (2D and 3D, visible light and infrared, etc.) to achieve reliable recognition in various environments. When only a single sensor is available, the robustness as well as efficacy of the recognition process suffer. In this paper, we focus on face recognition using images captured by a single 3D sensor and propose a method based on the use of region covariance matrixes and Gaussian mixture models (GMMs). All steps of the proposed framework are automated, and no metadata, such as pre-annotated eye, nose, or mouth positions is required, while only a very simple clustering-based face detection is performed. The framework computes a set of region covariance descriptors from local regions of different face image representations and then uses the unscented transform to derive low-dimensional feature vectors, which are finally modeled by GMMs. In the last step, a support vector machine classification scheme is used to make a decision about the identity of the input 3D facial image. The proposed framework has several desirable characteristics, such as an inherent mechanism for data fusion/integration (through the region covariance matrixes), the ability to explore facial images at different levels of locality, and the ability to integrate a domain-specific prior knowledge into the modeling procedure. Several normalization techniques are incorporated into the proposed framework to further improve performance. Extensive experiments are performed on three prominent databases (FRGC v2, CASIA, and UMB-DB) yielding competitive results.

Cervicofacial subcutaneous emphysema (SE) is primarily caused by dental treatment introducing gas into the subcutaneous tissue. Air rapidly dissects into the subcutaneous tissue with face and neck swelling, leading to respiratory distress, patient discomfort, and chest pain. Computed tomography (CT) can detect spreading SE patterns. However, the true volume of SE and the degree of air changes in the body over time remain unknown. We evaluated the healing process of SE and the temporal changes in the volume of emphysema in three cases detected using our hospital’s electronic health record systems based on inclusion and exclusion criteria over the past 10 years, with CT and three-dimensional (3D) images. The first case was a 46-year-old woman who presented with complaints of swelling from her right eyelid to the neck and clavicles, pain on swallowing, respiratory distress, and hoarseness. The second case was a 35-year-old man who presented with complaints of swelling over the face. The third case was a 36-year-old man who presented with complaints of swelling from the left cheek to the neck. CT revealed SE and pneumomediastinum in all cases. All the patients were administered an antibacterial drug. The CT and 3D images showed an improvement in emphysema 3 days after the onset, with more than half of the volume reduction in emphysema. This made it possible to evaluate the changes in the air content of SE. Observation with CT until the healing process of SE is completed is crucial, and 3D images also help evaluate changes over time.

Samples with 40% vol. of pores and a pore size distribution between 100 and 500 µm were produced by powder metallurgy from Ti6Al4V alloy powders. Sintering was performed at 1300 °C during one hour in an inert Argon atmosphere in a vertical dilatometer. The compressive strength and the porosity of these samples was investigated before and after compression tests through X-ray microtomography. The values of the elastic modulus (8GPa) and yield strength (80MPa) are within the range of those used in bone implants. Porosity leads to greater deformation whereas fracture of compacts occurs perpendicularly to the applied load. It was determined that the origin of the failure is generated by rupture of interparticle necks and, large pores enhance the propagation of cracks.

Objective: The aim of this study was to assess the role of multislice computed tomography (MSCT) using 2D and 3D images in evaluation of different types of Le Fort fractures. Subjects and methods: 30 cases referred from the Emergency unit in Zagazig University Hospital were included in this study, based on clinical evidence of facial trauma, they underwent multislice computed tomography (MSCT) examination and were shown to be positive for pterygoid fractures. All patients subjected to non contrast MSCT in axial cuts. Multiplanar reformatted (MPR) images were acquired using the machine software in sagittal and coronal planes. Finally images were transferred to a workstation for reconstruction of 3D images. Results: Sensitivity of multislice computed tomography (MSCT) in detecting compound Le Fort fractures for radiologists A, B and C was 94.4%, 66.7% and 100% respectively. Sensitivity of MSCT in detecting isolated Le Fort fractures for radiologists A, B and C was 100%. The difference between radiologists A, B and C in detecting Le Fort fractures types was insignificant. Good agreement between radiologists A, B, C and intraoperative findings. Conclusion: Both 2D-CT and 3D-CT are the best methods in imaging of Le Fort fractures.

The paper presents a new method of more precise estimation of the depth map in 3D videos. The novelty of the proposed approach lies in sophisticated combination of partial results obtained by selected existing passive and active 3D scanning methods. The aim of the combination is to overcome drawbacks of individual methods and this way to improve the accessible precision of the final depth map. The active method used is incoherent profilometry scanning which fails on surface discontinuities. As a passive method, a stereo pair matching is used. This method is currently the most widely applied method of depth map estimation in the field of 3D capturing and is available in various implementations. Unfortunately, it fails if there is a lack of identifiable corresponding points in the scanned scene. The paper provides a specific way of combining these methods to improve the accuracy and usability. The proposed innovative technique exploits the advantages of both approaches. Specifically, the more accurate depth profiles of individual discontinuous objects obtained from the active method, and information about mean depths of the objects from the stereo pair are combined. Two implementations of the passive method have been tested for combination with active scanning: matching from stereo pair, and SIFT. The paper includes a brief description of the active and passive methods used and a thorough explanation of their combination. As an example, the proposed method is tested on a simple scene whose nature enables straight assessment of the achieved accuracy. The choice of a suitable implementation of the passive component is also shown and discussed. The obtained results of individual existing methods used and of the proposed combined method are given and compared. To demonstrate the contribution of the proposed combined method, also a comparison with the results obtained with a commercial solution is presented with significantly good results.

The morphological tortuosity of a geodesic path in a medium can be defined as the ratio between its geodesic length and the Euclidean distance between its two extremities. Thus, the minimum tortuosity of all the geodesic paths into a medium in 2D or in 3D can be estimated by image processing methodsusing mathematical morphology. Considering a medium, the morphological tortuosities of its internal paths are estimated according to one direction, which is perpendicular to both starting and ending opposite extremities of the geodesicpaths. The used algorithm estimates the morphological tortuosities from geodesic distance maps, which are obtained from geodesic propagations. The shape of the propagated structuring element used to estimate the geodesic distance maps on a discrete grid has a direct influence on the morphological tortuosity and has to be chosen very carefully. The results of our algorithm is an image with pixels p having a value equal to the length of the shortest path containing p and connected to two considered opposite boundaries A and B of the image. The analysis of the histogram of the morphological tortuosities gives access to their statistical distribution. Moreover, for each tortuosity the paths can be extracted from the original image, which highlights the location of them into the sample. However, these geodesic paths have to be reconstructed for further processing. The extraction, because applying a threshold on the tortuosities, results in disconnected components, especially for highly tortuous paths. This reconstruction consists in reconnecting these components to the geodesic path linking the two opposite faces, by means of a backtracking algorithm.

Introducción: El sistema ventricular encefálico es muy complejo, y es especialmente difícil de comprender para los estudiantes de pregrado. Clásicamente, la anatomía ventricular puede enseñarse usando encéfalos cadavéricos, imágenes de tomografía o resonancia magnética. Presentamos nuestra experiencia con el uso de imágenes tridimensionales obtenidas mediante un sistema de neuronavegación. Material y métodos: Se obtuvieron imágenes de resonancia magnética de 3 pacientes. Las imágenes fueron introducidas en un sistema de neuronavegación y se reconstruyó específicamente el sistema ventricular encefálico y algunas estructuras gangliobasales. Posteriormente se solicitó la opinión de 38 estudiantes de pregrado que cursaban la materia neuroanatomía, sobre la utilidad de las imágenes en el estudio del sistema ventricular.Discusión: todas las imágenes obtenidas fueron de buena calidad, el 100% de los estudiantes manifestó que las imágenes eran muy útiles o esenciales para comprender cabalmente la anatomía ventricular. Conclusiones: el uso de imágenes obtenidas por un sistema de neuronavegación son útiles en la enseñanza de la anatomía del sistema ventricular encefálico. AIntroduction: Anatomy of cerebral ventricles is very complex. Classically, ventricular system anatomy has been taught employing cadaveric brains and CT or MRI images. We present 3D images of the ventricular system obtained by neuronavigation system and the results of its use in teaching anatomy of cerebral ventricles. Material and methods: Magnetic resonance images of three patients were obtained. These images were transferred to a neuronavigation system, and a 3D reconstruction of cerebral ventricles, were performed. Afterwards, 38 undergraduate students were required to give their opinion about how useful the images are in order to study the cerebral ventricles. Results: One hundred percent of the students agreed that the images were very useful or even essential to utterly comprehend the ventricular anatomy. Discussion: As other authors, we think that 3D images are very useful as a complement for teaching anatomy of cerebral ventricles. Conclusions: Employment of 3D images obtained in a computer system are useful for teaching the encephalic ventricular system anatomy, as a complementary tool.

In the framework of the Silent Wall ANR project, the CMM and the US2B are associated in order to characterize and to model fibrous media studying 3D images acquired with an X-Ray tomograph used by the US2B. The device can make 3D images of maximal 23043 voxels with resolutions in the range of 2 μm to 15 μm. Using mathematical morphology, measurements on the 3D X-Ray CT images are used to characterize materials. For example measuring the covariance on these images of an acoustic insulating material made of wooden fibres highlights the isotropy of the fibres orientations in the longitudinal planes which are perpendicular to the compression Oz axis. Moreover, it is possible to extract other morphological properties from these image processing methods such as the size distribution either of the fibres or of the pores by estimating the morphological opening granulometry of the considered medium. Using the theory of random sets introduced by Georges Matheron in the early 1970's, the aim of this work is to model such a fibrous material by parametric random media in 3D according to the prior knowledge of its morphological properties (covariance, porosity, size distributions, etc.). A Boolean model of random cylinders in 3D stacked in planes parallel to each other and perpendicular to the Oz compression axis is first considered. The granulometry results provide gamma distributions for the radii of the fibres. In addition, a uniform distribution of the orientations is chosen, according to the experimental isotropy measurements in the longitudinal planes. Finally the third statistical factor is the length distribution of the fibres which can be fitted by an exponential distribution. Thus it is possible to estimate the validity of this model first by trying to fit the experimental transverse and longitudinal covariances of the pores with the theoretical ones taking into account the statistical distributions of the dimensions of the random cylinders. The second method to validate the model consists in comparing morphological measurements (density profiles, covariance, opening granulometry, tortuosity, specific surface area) processed on real and on simulated media.

Minkowski functionals encompass standard geometric parameters such as volume, area, length and the Euler-Poincaré characteristic. Software tools for computing approximations of Minkowski functionals on binary 2D or 3D images are now available based on mathematical methods due to Serra, Lang and Ohser. Minkowski functionals can not be used to describe spatial heterogeneity of structures. This description can be performed by using Minkowski measures, which are local versions of Minkowski functionals. In this paper, we discuss how to extend the computation of Minkowski functionals to the computation of Minkowski measures. Approximations of Minkowski measures are computed using fltering and look-up table transformations. The final result is represented as a grey-level image. Approximation errors are investigated based on numerical examples. Convergence and non convergence of the measure approximations are discussed. The measure of surface area is used to describe spatial heterogeneity of a synthetic structure, and of an image of tomato pericarp.

Introduction: Nowadays virtual colonoscopy has become a reliable and efficient method of detecting primary stages of colon cancer such as polyp detection. One of the most important and crucial stages of virtual colonoscopy is colon segmentation because an incorrect segmentation may lead to a misdiagnosis. Materials and Methods: In this work, a hybrid method based on Geometric Deformable Models (GDM) in combination with an advanced region growing and thresholding methods is proposed. GDM are found to be an attractive tool for structural based image segmentation particularly for extracting the objects with complicated topology. There are two main parameters influencing the overall performance of GDM algorithm; the distance between the initial contour and the actual object’s contours and secondly the stopping term which controls the deformation. To overcome these limitations, a two stage hybrid based segmentation method is suggested to extract the rough but precise initial contours at the first stage of the segmentation. The extracted boundaries are smoothed and improved using a modified GDM algorithm by improving the stopping terms of the algorithm based on the gradient value of image voxels. Results: The proposed algorithm was implemented on forty data sets each containing 400-480 slices. The results show an improvement in the accuracy and smoothness of the extracted boundaries. The improvement obtained for the accuracy of segmentation is about 6% in comparison to the one achieved by the methods based on thresholding and region growing only. Discussion and Conclusion: The extracted contours using modified GDM are smoother and finer. The improvement achieved in this work on the performance of stopping function of GDM model together with applying two stage segmentation of boundaries have resulted in a great improvement on the computational efficiency of GDM algorithm while making smoother and finer colon borders.

Three-dimensional (3D) reconstruction of a tree canopy is an important step in order to measure canopy geometry, such as height, width, volume, and leaf cover area. In this research, binocular stereo vision was used to recover the 3D information of the canopy. Multiple images were taken from different views around the target. The Structure-from-motion (SfM) method was employed to recover the camera calibration matrix for each image, and the corresponding 3D coordinates of the feature points were calculated and used to recover the camera calibration matrix. Through this method, a sparse projective reconstruction of the target was realized. Subsequently, a ball pivoting algorithm was used to do surface modeling to realize dense reconstruction. Finally, this dense reconstruction was transformed to metric reconstruction through ground truth points which were obtained from camera calibration of binocular stereo cameras. Four experiments were completed, one for a known geometric box, and the other three were: a croton plant with big leaves and salient features, a jalapeno pepper plant with median leaves, and a lemon tree with small leaves. A whole-view reconstruction of each target was realized. The comparison of the reconstructed box’s size with the real box’s size shows that the 3D reconstruction is in metric reconstruction.

Abstract Background Further advances in modern microscopy are leading to teravoxel-sized tiled 3D images at high resolution, thus increasing the dimension of the stitching problem of at least two orders of magnitude. The existing software solutions do not seem adequate to address the additional requirements arising from these datasets, such as the minimization of memory usage and the need to process just a small portion of data. Results We propose a free and fully automated 3D Stitching tool designed to match the special requirements coming out of teravoxel-sized tiled microscopy images that is able to stitch them in a reasonable time even on workstations with limited resources. The tool was tested on teravoxel-sized whole mouse brain images with micrometer resolution and it was also compared with the state-of-the-art stitching tools on megavoxel-sized publicy available datasets. This comparison confirmed that the solutions we adopted are suited for stitching very large images and also perform well on datasets with different characteristics. Indeed, some of the algorithms embedded in other stitching tools could be easily integrated in our framework if they turned out to be more effective on other classes of images. To this purpose, we designed a software architecture which separates the strategies that use efficiently memory resources from the algorithms which may depend on the characteristics of the acquired images. Conclusions TeraStitcher is a free tool that enables the stitching of Teravoxel-sized tiled microscopy images even on workstations with relatively limited resources of memory (