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In this white paper, experts from the Digital Pathology Association (DPA) define terminology and concepts in the emerging field of computational pathology, with a focus on its application to histology images analyzed together with their associated patient data to extract information. This review offers a historical perspective and describes the potential clinical benefits from research and applications in this field, as well as significant obstacles to adoption. Best practices for implementing computational pathology workflows are presented. These include infrastructure considerations, acquisition of training data, quality assessments, as well as regulatory, ethical, and cyber‐security concerns. Recommendations are provided for regulators, vendors, and computational pathology practitioners in order to facilitate progress in the field. © 2019 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Spray deposit and superficial coverage play key roles in phytosanitary treatments. Their measurement is a quite complex task that requires adding suitable tracers to the mixture (deposit) and using some artificial targets (superficial coverage). With these laboratory tests, unit deposit values, measured in Petri dishes containing silicon oil, were correlated with percentage of covered surface, measured with water sensitive papers (WSPs) after spraying a water solution with red Ponceau at 2% concentration. An Albuz ATR 80 hollow cone nozzle was used at the spraying pressures of 0.3, 0.5, 1.0 and 1.5 MPa. The results showed a significant correlation between unit deposit d u (μL cm−2) and the fraction of covered surface x S ( d u = 2.2095 ⋅ x S − 0.3473 , R2 = 0.761, p-level

One of the biggest problems of agriculture is the reckless use of pesticides and their incorrect application with consequent waste of product and environmental pollution. The spray application characterization is a good preventive technique to limit the volume of a distributed product, to perform a more efficient application and to restrict the spray drift. Since there is no specific sampling technique useful for every context, it is necessary that every methodology is known in all its aspects before being employed. The colorimetry, fluorimetry and spectrometry methods are very accurate, but they are costly and time-consuming compared to a Water-Sensitive Paper (WSP) assessment performed by an image analysis software. This kind of software can detect and estimate many drops features using an image often obtained from a scanner. The objective of work was to develop a MATLAB code to evaluate the spray distribution over WSPs. After a pre-processing step in which the WSPs were isolated inside the image, the individual drops were identified using the difference between their color (blue) and the remaining dry part of the paper (yellow). Once the surface of every drop was estimated, it was possible to assess the number of the drops per cm2, the Normal Median Diameter (NMD) and the Normal Volume Diameter (VMD).

Desktop-publishing software and hardware has progressed to the point that many widely used word-processing programs are capable of printing high-quality digital images with many shades of gray from black to white. Accordingly, it should be relatively easy to print digital medical images on paper for reports, instructional materials, and in research notes. Components were assembled that were necessary for extracting image data from medical imaging devices and converting the data to a form usable by word-processing software. A system incorporating these components was implemented in a medical setting and has been operating for 18 months. The use of this system by medical staff has been monitored.

A novel method was developed for studying the ink-paper interface and the structural variations of a deposited layer of ink. Combining high-resolution x-ray tomography with laser ablation, the depth profile of ink (toner), i.e., its varying thickness, could be determined in a paper substrate. X-ray tomography was used to produce the 3D structure of paper with about 1 μm spatial resolution. Laser ablation combined with optical imaging was used to produce the 3D structure of the printed layer of ink on top of that paper with about 70 nm depth resolution. Ablation depth was calibrated with an optical profilometer. It can be concluded that a toner layer on a light-weight-coated paper substrate was strongly perturbed by protruding fibers of the base paper. Such fibers together with the surface topography of the base paper seem to be the major factors that control the leveling of toner and its penetration into a thinly coated paper substrate.

The results of the image analysis of handsheet obtained by different formers are presened in this paper. Handsheets are formed from the fibers obtained from the recycling process of prints produced in digital technique based on electrophotography with liquid and solid toner. The investigation results can be applied in the production of the recycled papers, and in the design of graphic products taking into consideration the postulates of the sustainable development.

Digital media such as World Wide Web or CD-ROMs enable us to publish and transfer computer graphics, digital images, or audio data in ways that were not available for paper media. Yet, paper still has many advantages. It is easier to carry, strong enough to survive dropping or bending, and it offers highest resolution for printed text and images. We have developed an augmented desk top interface, EnhancedDesk, which utilizes computer vision technology. EnhancedDesk smoothly links paper documents and digital documents. EnhancedDesk users can manipulate digital information projected onto the desk manually. Applications that show the effectiveness of EnhancedDesk are given.

xi, 498 ID: 768 Bibliographic Level Mode of Issuance: Monograph Includes bibliographical references and index. Full text also available on Internet. English

This paper reviews some of the digital optical cellular image processing techniques that have been proposed or experimentally demonstrated.

This editorial is an introduction to the special issue. A brief overview is given of the papers presented.

Describing and quantifying vascular canal orientation and volume of osteocyte lacunae in bone is important in studies of bone growth, mechanics, health and disease. It is also an important element in analysing fossil bone in palaeohistology, key to understanding the growth, life, and death of extinct animals. Often, bone microstructure is studied using two-dimensional (2D) sections, and three-dimensional (3D) shape and orientation of structures are estimated by modelling the structures using idealised geometries based on information from their cross sections. However, these methods rely on structures meeting strict geometric assumptions. Recently, 3D methods have been proposed which could provide a more accurate and robust approach to bone histology, but these have not been tested in direct comparison with their 2D counterparts in terms of accuracy and sensitivity to deviations from model assumptions. We compared 2D and 3D methodologies for estimating key microstructural traits using a combination of experimental and idealised test datasets. We generated populations of cylinders (canals) and ellipsoids (osteocyte lacunae), varying the cross-sectional aspect ratios of cylinders and orientation of ellipsoids to test sensitivity to deviations from cylindricality and longitudinal orientation, respectively. Using published methods, based on 2D sections and 3D datasets, we estimated cylinder orientation and ellipsoid volume. We applied the same methods to six CT datasets of duck cortical bone, using the full volumes for 3D measurements and single CT slices to represent 2D sections. Using in silico test datasets that did deviate from ideal cylinders and ellipsoids resulted in inaccurate estimates of cylinder or canal orientation, and reduced accuracy in estimates of ellipsoid and lacunar volume. These results highlight the importance of using appropriate 3D imaging and quantitative methods for quantifying volume and orientation of 3D structures and offer approaches to significantly enhance our understanding of bone physiology based on accurate measures for bone microstructures.

Fracturing two-dimensional random fiber networks of different densities (porosities) were statistically analyzed using both high-resolution finite element models and image analysis algorithms. Under small strains, the finite element fracture models revealed that networks with high relative densities were able to localize evolving fractures to small cracks while surprisingly larger cracks were required to localize fractures in networks of lower density. Further, it is indicated that the pore size distribution in fiber networks is rather diverse and can be captured using two mixed Gamma distributions; one part describing the background size distribution containing the vast majority of pores, and a second part describing the size distribution of larger pores and open regions. The second part covers less than 5% of the total network area but seems to be of paramount importance for the network’s global fracture behavior. It seems as a fiber network’s crack sensitivity is related to the average pore size in the second part of the mixed Gamma distribution. The analysis is remarkably consistent with reported experiments.

Biomass is a suitable energy source to reduce the carbon footprint and increase the use of renewable energy. However, the biomass exploitation is still slowed by many technical issues. In most practical applications, such as gasification or combustion devices, it is important to predict the fuel physical behavior in order to determine the emissions and heat release profile as well as for modeling and design purposes. Within this paper, the study of the dimensional evolution of a biomass fuel (beech wood) in pyrolysis and combustion processes were carried out with the use of the image analysis tool. Sizes from 15 mm to 300 mm characteristic length range were employed in the experiments and the collected data were related to the mass loss and temperature evolution of the biomass particle. It was found that for all the fuel sizes employed a similar volume reduction (60%–66%) was obtained at the end of pyrolysis. However, for the small particles with minor intra-particle gradients shrinkage took place mainly at the end of conversion, while for bigger particles the size variation patter was more linear. Furthermore, swelling was detected in the pyrolysis experiments, and it was higher for a bigger particle size, while cracking and fragmentation phenomena was observed for large wood logs combustion in the stove.

High-quality pollen is a prerequisite for plant reproductive success. Pollen viability and sterility can be routinely assessed using common stains and manual microscope examination, but with low overall statistical power. Current automated methods are primarily directed towards the analysis of pollen sterility, and high throughput solutions for both pollen viability and sterility evaluation are needed that will be consistent with emerging biotechnological strategies for crop improvement. Our goal is to refine established labelling procedures for pollen, based on the combination of fluorescein (FDA) and propidium iodide (PI), and to develop automated solutions for accurately assessing pollen grain images and classifying them for quality. We used open-source software programs (CellProfiler, CellProfiler Analyst, Fiji and R) for analysis of images collected from 10 pollen taxa labelled using FDA/PI. After correcting for image background noise, pollen grain images were examined for quality employing thresholding and segmentation. Supervised and unsupervised classification of per-object features was employed for the identification of viable, dead and sterile pollen. The combination of FDA and PI dyes was able to differentiate between viable, dead and sterile pollen in all the analysed taxa. Automated image analysis and classification significantly increased the statistical power of the pollen viability assay, identifying more than 75,000 pollen grains with high accuracy (R2 = 0.99) when compared to classical manual counting. Overall, we provide a comprehensive set of methodologies as baseline for the automated assessment of pollen viability using fluorescence microscopy, which can be combined with manual and mechanized imaging systems in fundamental and applied research on plant biology. We also supply the complete set of pollen images (the FDA/PI pollen dataset) to the scientific community for future research. Electronic supplementary material The online version of this article (10.1007/s00497-020-00398-6) contains supplementary material, which is available to authorized users.

Significance: Accessible tools are needed for rapid, non-destructive imaging of patient-derived cancer organoid (PCO) treatment response to accelerate drug discovery and streamline treatment planning for individual patients. Aim: To segment and track individual PCOs with wide-field one-photon redox imaging to extract morphological and metabolic variables of treatment response. Approach: Redox imaging of the endogenous fluorophores, nicotinamide dinucleotide (NADH), nicotinamide dinucleotide phosphate (NADPH), and flavin adenine dinucleotide (FAD), was used to monitor the metabolic state and morphology of PCOs. Redox imaging was performed on a wide-field one-photon epifluorescence microscope to evaluate drug response in two colorectal PCO lines. An automated image analysis framework was developed to track PCOs across multiple time points over 48 h. Variables quantified for each PCO captured metabolic and morphological response to drug treatment, including the optical redox ratio (ORR) and organoid area. Results: The ORR (NAD(P)H/(FAD + NAD(P)H)) was independent of PCO morphology pretreatment. Drugs that induced cell death decreased the ORR and growth rate compared to control. Multivariate analysis of redox and morphology variables identified distinct PCO subpopulations. Single-organoid tracking improved sensitivity to drug treatment compared to pooled organoid analysis. Conclusions: Wide-field one-photon redox imaging can monitor metabolic and morphological changes on a single organoid-level, providing an accessible, non-destructive tool to screen drugs in patient-matched samples.

Smartphone based devices (SBDs) have the potential to revolutionize food safety control by empowering citizens to perform screening tests. To achieve this, it is of paramount importance to understand current research efforts and identify key technology gaps. Therefore, a systematic review of optical SBDs in the food safety sector was performed. An overview of reviewed SBDs is given focusing on performance characteristics as well as image analysis procedures. The state-of-the-art on commercially available SBDs is also provided. This analysis revealed several important technology gaps, the most prominent of which are: (i) the need to reach a consensus regarding optimal image analysis, (ii) the need to assess the effect of measurement variation caused by using different smartphones and (iii) the need to standardize validation procedures to obtain robust data. Addressing these issues will drive the development of SBDs and potentially unlock their massive potential for citizen-based food control., Highlights • Optical smartphone based sensors in the food safety field are systematically reviewed. • Recommendations on image analysis optimization are given. • The analytical performance of smartphone based sensors is discussed. • Available commercial devises are critically compared.

During metastasis, tumor cells dynamically change their cytoskeleton to traverse through a variety of non-adherent microenvironments, including the vasculature or lymphatics. Due to the challenges of imaging drift in non-adhered tumor cells, the dynamic cytoskeletal phenotypes are poorly understood. We present a new approach to analyze the dynamic cytoskeletal phenotypes of non-adhered cells that support microtentacles (McTNs), which are cell surface projections implicated in metastatic reattachment. Combining a recently-developed cell tethering method with a novel image analysis framework allowed McTN attribute extraction. Full cell outlines, number of McTNs, and distance of McTN tips from the cell body boundary were calculated by integrating a rotating anisotropic filtering method for identifying thin features with retinal segmentation and active contour algorithms. Tethered cells behave like free-floating cells; however tethering reduces cell drift and improves the accuracy of McTN measurements. Tethering cells does not significantly alter McTN number, but rather allows better visualization of existing McTNs. In drug treatment experiments, stabilizing tubulin with paclitaxel significantly increases McTN length, while destabilizing tubulin with colchicine significantly decreases McTN length. Finally, we quantify McTN dynamics by computing the time delay autocorrelations of 2 composite phenotype metrics (cumulative McTN tip distance, cell perimeter:cell body ratio). Our automated analysis demonstrates that treatment with paclitaxel increases total McTN amount and colchicine reduces total McTN amount, while paclitaxel also reduces McTN dynamics. This analysis method enables rapid quantitative measurement of tumor cell drug responses within non-adherent microenvironments, using the small numbers of tumor cells that would be available from patient samples.

The directions of the ecological sustainability in printing reproduction are in the area of the application of the renewable and recycled raw materials, in the decrease of the energy consumption, the usage of the energy from the renewable sources and in the production without waste. This article presents the research results of voltage changes of the intermediate cylinder in indirect electrophotography with liquid toner on dirt count and area on handsheet made from fibers after prints pulping and flotation, brightness and effective residual ink concentration. Since on the indirect transfer of ElectroInk except the voltage of the intermediate cylinder also impacts temperature, its influence on the dirt count and area is showed. Uncoated and both side coated substrates were used for printing. The results show that changes in voltage of the intermediate cylinder in the printing affects the characteristics of pulped and floated fibers and dirt count and area on handsheets. Dominant factor of studied process is surface treatment of the printing substrate. Maximum efficiency of deinking flotation (87.7%) was observed on non coated paper print, at the voltage of the intermediate cylinder of 700V. The efficiency of deinking flotation on both sides coated paper prints in dependence on the voltage of the intermediate cylinder in most cases is below 10%. The results show that an increase in temperature of the intermediate cylinder increases dirt count and area on handsheetst after pulping prints under experimental conditions. Increased efficiency of flotation was found for print obtained at a lower temperature of the intermediate cylinder.

Urinary stones composed of uric acid can be treated medically. Prediction of uric acid stone type is, therefore, desirable when a urinary stone is diagnosed with unenhanced CT. The purpose of the present study was to describe single-energy thin slice quantitative CT parameters of urinary stones correlated to chemical stone type and to develop a method to distinguish pure uric acid stones (UA) from other stones (non-UA/Mix). Unenhanced thin slice single-energy CT images of 126 urinary stones (117 patients) with known chemical stone type were retrospectively included in the study. Among the included stones, 22 were UA and 104 were non-UA/Mix. The included CT images and Laplacian filtered images of the stones were quantitatively analyzed using operator-independent methods. A post hoc classification method for pure UA stones was created using a combination of cutoff values for the peak attenuation and peak point Laplacian. The stone types differed in most quantitative image characteristics including mean attenuation (p

The data set contains images of leaf venation networks obtained from tree species in Malaysian Borneo. The data set contains 726 leaves from 295 species comprising 50 families, sampled from eight forest plots in Sabah. Image extents are approximately 1 × 1 cm, or 50 megapixels. All images contain a region of interest in which all veins have been hand traced. The complete data set includes over 30 billion pixels, of which more than 600 million have been validated by hand tracing. These images are suitable for morphological characterization of these species, as well as for training of machine‐learning algorithms that segment biological networks from images. Data are made available under the Open Data Commons Attribution License. You are free to copy, distribute, and use the database; to produce works from the database; and to modify, transform, and build upon the database. You must attribute any public use of the database, or works produced from the database, in the manner specified in the license. For any use or redistribution of the database, or works produced from it, you must make clear to others the license of the database and keep intact any notices on the original database.

Collagen remodeling occurs in many prostate pathologies; however, the underlying structural architecture in both normal and diseased prostatic tissues is largely unexplored. Here, we use second-harmonic generation (SHG) microscopy to specifically probe the role of the proteoglycan decorin (Dcn) on collagen assembly in a wild type (wt) and Dcn null mouse (Dcn − / − ). Dcn is required for proper organization of collagen fibrils as it regulates size by forming an arch-like structure at the end of the fibril. We have utilized SHG metrics based on emission directionality (forward–backward ratio) and relative conversion efficiency, which are both related to the SHG coherence length, and found more disordered fibril organization in the Dcn − / − . We have also used image analysis readouts based on entropy, multifractal dimension, and wavelet transforms to compare the collagen fibril/fiber architecture in the two models, where all these showed that the Dcn − / − prostate comprised smaller and more disorganized collagen structures. All these SHG metrics are consistent with decreased SHG phase matching in the Dcn − / − and are further consistent with ultrastructural analysis of collagen in this model in other tissues, which show a more random distribution of fibril sizes and their packing into fibers. As Dcn is a known tumor suppressor, this work forms the basis for future studies of collagen remodeling in both malignant and benign prostate disease.

The aim of the present work was to develop a method based on image analysis for describing soil detachment caused by the impact of a single water drop. The method consisted of recording tracks made by splashed particles on blotting paper under an optical microscope. The analysis facilitated division of the recorded particle tracks on the paper into drops, “comets” and single particles. Additionally, the following relationships were determined: (i) the distances of splash; (ii) the surface areas of splash tracks into relation to distance; (iii) the surface areas of the solid phase transported over a given distance; and (iv) the ratio of the solid phase to the splash track area in relation to distance. Furthermore, the proposed method allowed estimation of the weight of soil transported by a single water drop splash in relation to the distance of the water drop impact. It was concluded that the method of image analysis of splashed particles facilitated analysing the results at very low water drop energy and generated by single water drops.

Highlight Image Harvest is an open-source software for high-throughput image processing and analysis that is integrated with the Open Science Grid and provides computational resources to process large image datasets., High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources required for processing large image datasets at no cost. Image Harvest also offers functionalities to extract digital traits from images to interpret plant architecture-related characteristics. To demonstrate the applications of these digital traits, a rice (Oryza sativa) diversity panel was phenotyped and genome-wide association mapping was performed using digital traits that are used to describe different plant ideotypes. Three major quantitative trait loci were identified on rice chromosomes 4 and 6, which co-localize with quantitative trait loci known to regulate agronomically important traits in rice. Image Harvest is an open-source software for high-throughput image processing that requires a minimal learning curve for plant biologists to analyzephenomics datasets.

O pinhão manso (Jatropha curcas L.) apresenta elevado potencial para produção de biocombustível; porém, existem poucos estudos relacionados à avaliação da qualidade de suas sementes. Assim, a pesquisa objetivou estudar os procedimentos para a condução do teste de tetrazólio e verificar a eficiência dos testes de tetrazólio e de raios X para a avaliação da viabilidade de sementes desta espécie. Para o teste de tetrazólio, foi comparado o pré-condicionamento entre papel e imersão em água, até que as sementes atingissem os teores de água de 30% e 40%. Após esta etapa, o tegumento das sementes foi retirado manualmente e os embriões foram imersos em solução de 2,3,5 trifenil cloreto de tetrazólio nas concentrações de 0,075% e 0,5%, por 120 minutos, a 40ºC. Os resultados do teste de germinação foram confrontados com os resultados do teste de tetrazólio. A hidratação entre papel, até as sementes atingirem 30% de água e a coloração do embrião em solução 0,5% de tetrazólio, durante 120 minutos, no escuro, a 40ºC, produzem informações consistentes. As sementes de pinhão manso foram submetidas ao teste de raios X, na intensidade de 25 Kv durante 60s; posteriormente, foi realizado o teste de germinação, relacionando-se os resultados obtidos nesses dois testes. Concluiu-se que é possível utilizar o teste de tetrazólio e de raios X para avaliar a viabilidade das sementes de pinhão manso. The Jatropha curcas L. presents a great potential for fuel, but there are few studies to assess seed quality of this species. Therefore, this research aimed to study the performance of the tetrazolium salt test procedures and to verify the efficiency of the X-ray test to evaluate the seed viability of this species. Seeds were hydrated between paper towel and immersed in water to reach 30 and 40% m.c.. Following, seed coat was removed manually and seeds were immersed in 0,075 and 0,5% tetrazolium solutions for 120 min., respectively, at 40ºC. Best results of tetrazolium test comprised the hydration between paper, until the seeds reach 30% m.c. and coloration in contact with a solution of 0,5%. The Jatropha curcas L. seeds were also submitted to X-ray test, in intensity of the 25Kv for 60s. Results of tetrazolium and X-ray tests were compared to germination and it was shown that both are efficient to assess Jatropha curcas L. seeds viability.

Significance: Fluorescence lifetime imaging microscopy (FLIM) is a powerful technique to distinguish the unique molecular environment of fluorophores. FLIM measures the time a fluorophore remains in an excited state before emitting a photon, and detects molecular variations of fluorophores that are not apparent with spectral techniques alone. FLIM is sensitive to multiple biomedical processes including disease progression and drug efficacy. Aim: We provide an overview of FLIM principles, instrumentation, and analysis while highlighting the latest developments and biological applications. Approach: This review covers FLIM principles and theory, including advantages over intensity-based fluorescence measurements. Fundamentals of FLIM instrumentation in time- and frequency-domains are summarized, along with recent developments. Image segmentation and analysis strategies that quantify spatial and molecular features of cellular heterogeneity are reviewed. Finally, representative applications are provided including high-resolution FLIM of cell- and organelle-level molecular changes, use of exogenous and endogenous fluorophores, and imaging protein-protein interactions with Förster resonance energy transfer (FRET). Advantages and limitations of FLIM are also discussed. Conclusions: FLIM is advantageous for probing molecular environments of fluorophores to inform on fluorophore behavior that cannot be elucidated with intensity measurements alone. Development of FLIM technologies, analysis, and applications will further advance biological research and clinical assessments.

Limited studies have shown that some patients with pancreatic adenocarcinoma (PAC) may benefit from treatment with tamoxifen. PAC has been shown to be largely negative for estrogen receptor alpha (ER-alpha). The aim of this pilot study was to investigate ER-beta expression in human PAC. Sections of tissue microarray with 18 evaluable cases of human PAC were stained by immunohistochemistry (IHC) for ER-beta1, ER-beta2, ER-beta5, and Cyclin A. The levels of ER-beta isoform expression and the S-phase fraction (SPF) were determined using quantitative digital image analysis. Higher mean and median ER-beta2 levels correlated with male sex (p = 0.057 and p = 0.035, respectively), older age (p = 0.005 and p = 0.006, respectively), and lower pT stage (p = 0.008 and p = 0.009). Mean and median ER-beta5 levels correlated negatively with SPF (p = 0.021 and p = 0.047, respectively). Mean ER-beta1 expression did not correlate with any of the above mentioned clinicopathologic factors. The findings in this pilot study, although should be considered preliminary, suggest that some ER-beta isoforms may play a role in the biology of PAC. Additional larger studies are needed to confirm our findings, and to determine whether ER-beta may be considered for future targeted therapy.

Background Fungi have diverse biotechnological applications in, among others, agriculture, bioenergy generation, or remediation of polluted soil and water. In this context, culture media based on color change in response to degradation of dyes are particularly relevant; but measuring dye decolorisation of fungal strains mainly relies on a visual and semiquantitative classification of color intensity changes. Such a classification is a subjective, time-consuming and difficult to reproduce process. Results DecoFungi is the first, at least up to the best of our knowledge, application to automatically characterise dye decolorisation level of fungal strains from images of inoculated plates. In order to deal with this task, DecoFungi employs a deep-learning model, accessible through a user-friendly web interface, with an accuracy of 96.5%. Conclusions DecoFungi is an easy to use system for characterising dye decolorisation level of fungal strains from images of inoculated plates.

The discovery and clinical application of molecular biomarkers in solid tumors, increasingly relies on nucleic acid extraction from FFPE tissue sections and subsequent molecular profiling. This in turn requires the pathological review of haematoxylin & eosin (H&E) stained slides, to ensure sample quality, tumor DNA sufficiency by visually estimating the percentage tumor nuclei and tumor annotation for manual macrodissection. In this study on NSCLC, we demonstrate considerable variation in tumor nuclei percentage between pathologists, potentially undermining the precision of NSCLC molecular evaluation and emphasising the need for quantitative tumor evaluation. We subsequently describe the development and validation of a system called TissueMark for automated tumor annotation and percentage tumor nuclei measurement in NSCLC using computerized image analysis. Evaluation of 245 NSCLC slides showed precise automated tumor annotation of cases using Tissuemark, strong concordance with manually drawn boundaries and identical EGFR mutational status, following manual macrodissection from the image analysis generated tumor boundaries. Automated analysis of cell counts for % tumor measurements by Tissuemark showed reduced variability and significant correlation (p < 0.001) with benchmark tumor cell counts. This study demonstrates a robust image analysis technology that can facilitate the automated quantitative analysis of tissue samples for molecular profiling in discovery and diagnostics.

The aim of this study was the identification of proteins differentially represented in the serum proteome of seropositive dogs with (Group 1) and without (Group 2) clinical-pathologic signs consistent with ehrlichiosis compared to healthy control dogs. Serum samples were collected from 20 dogs of various breeds with naturally occurring ehrlichiosis (10 dogs belonged to Group 1 and 10 to Group 2) and 10 healthy dogs. Two-dimensional electrophoresis (2DE) of pooled serum for each of the group of dogs were run in triplicate. 2D image analysis showed 39 spots differently expressed between Group 1 and Group 2 compared with healthy ones. Mass spectrometry analysis allowed identification of 6 proteins: albumin, haptoglobin (Hp), alpha-l-antitrypsin (AAT), Retinol Binding Protein 4 (RBP-4), alpha-l-acid glycoprotein (AGP) and vitamin D-binding protein (VDBP). When a confirmatory study was performed for albumin, Hp, AAT and RBP-4 by using different assays, significant differences (P < 0.05) between diseased and healthy groups were observed. It can be concluded that there are significant changes in the serum proteome of dogs with ehrlichiosis with modifications in proteins related with the acute phase response such as Hp, albumin and AGP, with vitamin A transport such as RBP-4, with inhibitors of serine proteases and anti-inflammatory proteins such as AAT, and vitamin D metabolism and actin scavengers such as VDBP. "Ministerio de Economia y Competividad" of Spain Fundacion Seneca - 19894/GERM/15

Optical coherence tomography angiography (OCTA) provides in-vivo images of microvascular perfusion in high resolution. For its application to basic and clinical research, an automatic and robust quantification of the capillary architecture is mandatory. Only this makes it possible to reliably analyze large amounts of image data, to establish biomarkers, and to monitor disease developments. However, due to its optical properties, OCTA images of skin often suffer from a poor signal-to-noise ratio and contain imaging artifacts. Previous work on automatic vessel segmentation in OCTA mostly focuses on retinal and cerebral vasculature. Its applicability to skin and, furthermore, its robustness against imaging artifacts had not been systematically evaluated. We propose a segmentation method that improves the quality of vascular quantification in OCTA images even if corrupted by imaging artifacts. Both the combination of image processing methods and the choice of their parameters are systematically optimized to match the manual labeling of an expert for OCTA images of skin. The efficacy of this optimization-based vessel segmentation is further demonstrated on sample images as well as by a reduced error of derived quantitative vascular network characteristics.

Highlight The method presented analyses root scans automatically, distinguishes primary from lateral roots, and quantifies a broad range of traits for individual primary roots and their associated lateral roots., This paper outlines a numerical scheme for accurate, detailed, and high-throughput image analysis of plant roots. In contrast to existing root image analysis tools that focus on root system-average traits, a novel, fully automated and robust approach for the detailed characterization of root traits, based on a graph optimization process is presented. The scheme, firstly, distinguishes primary roots from lateral roots and, secondly, quantifies a broad spectrum of root traits for each identified primary and lateral root. Thirdly, it associates lateral roots and their properties with the specific primary root from which the laterals emerge. The performance of this approach was evaluated through comparisons with other automated and semi-automated software solutions as well as against results based on manual measurements. The comparisons and subsequent application of the algorithm to an array of experimental data demonstrate that this method outperforms existing methods in terms of accuracy, robustness, and the ability to process root images under high-throughput conditions.

Increased adipocyte size and number are associated with many of the adverse effects observed in metabolic disease states. While methods to quantify such changes in the adipocyte are of scientific and clinical interest, manual methods to determine adipocyte size are both laborious and intractable to large scale investigations. Moreover, existing computational methods are not fully automated. We, therefore, developed a novel automatic method to provide accurate measurements of the cross-sectional area of adipocytes in histological sections, allowing rapid high-throughput quantification of fat cell size and number. Photomicrographs of H&E-stained paraffin sections of murine gonadal adipose were transformed using standard image processing/analysis algorithms to reduce background and enhance edge-detection. This allowed the isolation of individual adipocytes from which their area could be calculated. Performance was compared with manual measurements made from the same images, in which adipocyte area was calculated from estimates of the major and minor axes of individual adipocytes. Both methods identified an increase in mean adipocyte size in a murine model of obesity, with good concordance, although the calculation used to identify cell area from manual measurements was found to consistently over-estimate cell size. Here we report an accurate method to determine adipocyte area in histological sections that provides a considerable time saving over manual methods.

Objective: To evaluate the diagnostic efficacy of thin-slice (1mm) axial proton density-weighted (PDW) MRI of the knee for meniscal tear detection and classification. Methods: We prospectively assessed pre-operative MR images of 58 patients (41 males, 17 females; age range 18-62 years) with arthroscopically confirmed meniscal tear. First, we evaluated the performance of the sagittal and thin-slice axial MR images for the diagnosis of meniscal tears. Second, we compared the correlation of tear types presumed from sagittal and axial MRI with arthroscopy and tear classification from axial MRI. Tears were classified on the sagittal plane and the axial plane separately. The diagnostic performance and tear classification were compared statistically with arthroscopy results, which is accepted as the standard of reference. Results: 8 of 58 patients were removed from the study group because they had complex or degenerative tears. A total of 62 tears were detected with arthroscopy in 50 patients. On the sagittal images, sensitivity and specificity values were 90.62% and 70.37%, respectively, for medial meniscus tears and 72.73% and 77.14%, respectively, for lateral meniscus tears. The corresponding values for axial images were 97.30% and 84.00%, respectively, for medial meniscus tears and 95.65% and 80.50%, respectively, for lateral meniscus tears. There was no significant difference in tear classification between the arthroscopy results and the thin-slice axial PDW MRI results (p > 0.05). Conclusion: thin-slice axial PDW MRI increases the sensitivity and specificity of meniscal tear detection and especially classification, which is important for surgical procedure decisions.

When analyzing computer simulations of mixtures of lipids and water, the questions to be answered are often of a morphological nature. They can deal with global properties, like the kind of phase that is adopted or the presence or absence of certain key features like a pore or stalk, or with local properties, like the local curvature present at a particular part of the lipid/water interface. While in principle all of the information relating to the global and local morphological properties of a system can be obtained from the set of atomic coordinates generated by a computer simulation, the extraction of this information is a tedious task that usually involves using a visualization program and performing the analysis by eye. Here we present a tool that employs the technique of morphological image analysis (MIA) to automatically extract the global morphology-as given by Minkowski functionals-from a set of atomic coordinates, and creates an image of the system onto which the local curvatures are mapped as a color code.

As part of a training set for automated image analysis, crystallization screening experiments for 269 different macromolecules were visually analyzed and a set of crystal images extracted. Outcomes and trends are analyzed., In the automated image analysis of crystallization experiments, representative examples of outcomes can be obtained rapidly. However, while the outcomes appear to be diverse, the number of crystalline outcomes can be small. To complement a training set from the visual observation of 147 456 crystallization outcomes, a set of crystal images was produced from 106 and 163 macromolecules under study for the North East Structural Genomics Consortium (NESG) and Structural Genomics of Pathogenic Protozoa (SGPP) groups, respectively. These crystal images have been combined with the initial training set. A description of the crystal-enriched data set and a preliminary analysis of outcomes from the data are described.

International audience; Using a pilot scale continuous system with activated sludge, the effect of the variability of non-pretreated synthetic textile wastewater containing reactive dyes on the pollution bio-removal and on the characteristics of activated sludge (sludge volume index, floc size and shape, filamentous bacteria abundance) has been monitored. Off-line batch respirometry tests have been used in parallel to assess the toxic effects of some of the reactive dyes. Experiments were run by increasing the concentration of a single dye (Run 1) and by feeding with a non-repetitive (Run 2) or a repetitive (Run 3) sequence of dyes. In all runs dyes were added to a synthetic wastewater of constant composition. Although the biomass was significantly upset by some of the dyes, it was able to cope up with the variations of their chemistry and remained active throughout the experiments and could contribute to COD removal. The dyes were partially adsorbed but not degraded by the micro-organisms.

The purpose was to create a three-dimensional (3-D) model of circumferential aqueous humor outflow (AHO) in a living human eye with an automated detection algorithm for Schlemm’s canal (SC) and first-order collector channels (CC) applied to spectral-domain optical coherence tomography (SD-OCT). Anterior segment SD-OCT scans from a subject were acquired circumferentially around the limbus. A Bayesian Ridge method was used to approximate the location of the SC on infrared confocal laser scanning ophthalmoscopic images with a cross multiplication tool developed to initiate SC/CC detection automated through a fuzzy hidden Markov Chain approach. Automatic segmentation of SC and initial CC’s was manually confirmed by two masked graders. Outflow pathways detected by the segmentation algorithm were reconstructed into a 3-D representation of AHO. Overall, only

Evaluation of segmentation algorithms usually involves comparisons of segmentations to gold-standard delineations without regard to the ultimate medical decision-making task. We compare two segmentation evaluations methods-a Dice similarity coefficient (DSC) evaluation and a diagnostic classification task-based evaluation method using lesions from breast computed tomography. In our investigation, we use results from two previously developed lesion-segmentation algorithms [a global active contour model (GAC) and a global with local aspects active contour model]. Although similar DSC values were obtained (0.80 versus 0.77), we show that the global + local active contour (GLAC) model, as compared with the GAC model, is able to yield significantly improved classification performance in terms of area under the receivers operating characteristic (ROC) curve in the task of distinguishing malignant from benign lesions. [Area under the [Formula: see text] compared to 0.63, [Formula: see text]]. This is mainly because the GLAC model yields better detailed information required in the calculation of morphological features. Based on our findings, we conclude that the DSC metric alone is not sufficient for evaluating segmentation lesions in computer-aided diagnosis tasks.

Particle_in_Cell-3D is a powerful method to quantify the cellular uptake of nanoparticles. It combines the advantages of confocal fluorescence microscopy with fast and precise semi-automatic image analysis. In this work we present how this method was applied to investigate the impact of 310 nm silica nanoparticles on human vascular endothelial cells (HUVEC) in comparison to a cancer cell line derived from the cervix carcinoma (HeLa). The absolute number of intracellular silica nanoparticles within the first 24 h was determined and shown to be cell type-dependent. As a second case study, Particle_in_Cell-3D was used to assess the uptake kinetics of 8 nm and 30 nm ceria nanoparticles interacting with human microvascular endothelial cells (HMEC-1). These small nanoparticles formed agglomerates in biological medium, and the particles that were in effective contact with cells had a mean diameter of 417 nm and 316 nm, respectively. A significant particle size-dependent effect was observed after 48 h of interaction, and the number of intracellular particles was more than four times larger for the 316 nm agglomerates. Interestingly, our results show that for both particle sizes there is a maximum dose of intracellular nanoparticles at about 24 h. One of the causes for such an interesting and unusual uptake behavior could be cell division.

Although the pathogenesis of bipolar disorder is still not completely understood, there is evidence from imaging studies that abnormalities in inter-hemispheric communication may play a major role in the pathophysiology of bipolar disorder. In the present review, we discuss the most consistent findings from diffusion imaging studies exploring corpus callosum integrity in bipolar disorder.

Background: There are 600,000 new malaria cases daily worldwide. The gold standard for estimating the parasite burden and the corresponding severity of the disease consists in manually counting the number of parasites in blood smears through a microscope, a process that can take more than 20 minutes of an expert microscopist’s time. Objective: This research tests the feasibility of a crowdsourced approach to malaria image analysis. In particular, we investigated whether anonymous volunteers with no prior experience would be able to count malaria parasites in digitized images of thick blood smears by playing a Web-based game. Methods: The experimental system consisted of a Web-based game where online volunteers were tasked with detecting parasites in digitized blood sample images coupled with a decision algorithm that combined the analyses from several players to produce an improved collective detection outcome. Data were collected through the MalariaSpot website. Random images of thick blood films containing Plasmodium falciparum at medium to low parasitemias, acquired by conventional optical microscopy, were presented to players. In the game, players had to find and tag as many parasites as possible in 1 minute. In the event that players found all the parasites present in the image, they were presented with a new image. In order to combine the choices of different players into a single crowd decision, we implemented an image processing pipeline and a quorum algorithm that judged a parasite tagged when a group of players agreed on its position. Results: Over 1 month, anonymous players from 95 countries played more than 12,000 games and generated a database of more than 270,000 clicks on the test images. Results revealed that combining 22 games from nonexpert players achieved a parasite counting accuracy higher than 99%. This performance could be obtained also by combining 13 games from players trained for 1 minute. Exhaustive computations measured the parasite counting accuracy for all players as a function of the number of games considered and the experience of the players. In addition, we propose a mathematical equation that accurately models the collective parasite counting performance. Conclusions: This research validates the online gaming approach for crowdsourced counting of malaria parasites in images of thick blood films. The findings support the conclusion that nonexperts are able to rapidly learn how to identify the typical features of malaria parasites in digitized thick blood samples and that combining the analyses of several users provides similar parasite counting accuracy rates as those of expert microscopists. This experiment illustrates the potential of the crowdsourced gaming approach for performing routine malaria parasite quantification, and more generally for solving biomedical image analysis problems, with future potential for telediagnosis related to global health challenges. [J Med Internet Res 2012;14(6):e167]

his work focuses on the use of chemometric techniques for identifying activated sludge process abnormalities. Chemometric methods combined with image analysis can improve activated sludge systems monitoring and minimize the need of analytical measurements. For that purpose data was collected from aggregated and filamentous biomass, biomass composition on Gram-positive/Gram-negative bacteria and viable/damaged bacteria, and operational parameters. Principal component analysis (PCA) was subsequently applied to identify activated sludge abnormalities, allowing the identification of several disturbances, namely filamentous bulking, pinpoint flocs formation, and zoogleal bulking as well as normal conditions by grouping the collected samples in corresponding clusters., The authors acknowledge the financial support to D.P. Mesquita through the grant SFRH/BD/32329/2006 and the project PTDC/EBB-EBI/103147/2008 provided by Fundação para a Ciência e a Tecnologia (Portugal).

Background: Fibrosis is associated with various cardiac pathologies and dysfunction. Current quantification methods are time-consuming and laborious. We describe a semi-automated quantification technique for myocardial fibrosis and validated this using traditional methods.Methods: Pulmonary Hypertension (PH) was induced in adult Wistar rats by subcutaneous monocrotaline (MCT) injection (40 mg/kg). Cryosections of myocardial tissue (5 μm) of PH rats (n=9) and controls (n=9) were stained using Picrosirius red and scanned with a digital microscopic Mirax slide scanner. From these sections 21 images were taken randomly of each heart. Using ImageJ software a macro for automated image analysis of the amount of fibrosis was developed. For comparison, fibrosis was quantified using traditional polarisation microscopy. Both methods were correlated and validated against stereology as the gold standard. Furthermore, the method was tested in paraffin-embedded human tissues.Results: Automated analysis showed a significant increase of fibrosis in PH hearts vs. control. Automated analysis correlated with traditional polarisation and stereology analysis (r2=0.92 and r2=0.95, respectively). In human heart, lungs, kidney and liver, a similar correlation with stereology (r2=0.91) was observed. Time required for automated analysis was 22 and 33% of the time needed for stereology and polarisation analysis, respectively.Conclusion: Automated quantification of fibrosis is feasible, objective and time-efficient.

Purpose The purpose of the study was to present a methodology for the processing of Magnetic Resonance Imaging (MRI) data for the quantification of the dosage form matrix evolution during drug dissolution. The results of the study were verified by comparison with other approaches presented in literature. Methods A commercially available, HPMC-based quetiapine fumarate tablet was studied with a 4.7T MR system. Imaging was performed inside an MRI probe-head coupled with a flow-through cell for 12 h in circulating water. The images were segmented into three regions using threshold-based segmentation algorithms due to trimodal structure of the image intensity histograms. Results Temporal evolution of dry glassy, swollen glassy and gel regions was monitored. The characteristic features were observed: initial high expansion rate of the swollen glassy and gel layers due to initial water uptake, dry glassy core disappearance and maximum area of swollen glassy region at 4 h, and subsequent gel layer thickness increase at the expense of swollen glassy layer. Conclusions The temporal evolution of an HPMC-based tablet by means of noninvasive MRI integrated with USP Apparatus 4 was found to be consistent with both the theoretical model based on polymer disentanglement concentration and experimental VIS/FTIR studies.

The effect of aluminum on agglomeration in the sludge bed and chemical oxygen demand (COD) removal efficiency in laboratory-scale upflow anaerobic sludge blanket (UASB) reactors treating low-strength synthetic wastewater (approximately 665 to 738 mg/L of COD) was investigated. Continuous application of aluminum chloride (200 mg/L) caused poor COD removal, less sludge density, and adversely affected agglomeration in the sludge bed. An adverse effect on granulation also was observed when 300 mg/L aluminum chloride was added only during the startup, and the effect continued even after it was discontinued. A lower concentration of aluminum chloride (50 mg/L) added for 30 days after the reactors reached steady-state did not affect the COD removal efficiency, but adversely affected the growth of agglomerates and caused temporary degeneration of existing agglomerates. The adverse effect of aluminum appeared to stem from the precipitation of aluminum hydroxide on the surfaces of agglomerates. The effect of aluminum on agglomeration was shown to be a function of influent strength. Water Environ. Res., 82, 715 (2010).

A system for scoring images based on the likelihood of containing crystalline material is described. A simulation carried out on a real set of crystallization images demonstrates the utility of such a system in high-throughput environments by substantially reducing the manual workload necessary to detect crystals for X-ray screening., The ability of computers to learn from and annotate large databases of crystallization-trial images provides not only the ability to reduce the workload of crystallization studies, but also an opportunity to annotate crystallization trials as part of a framework for improving screening methods. Here, a system is presented that scores sets of images based on the likelihood of containing crystalline material as perceived by a machine-learning algorithm. The system can be incorporated into existing crystallization-analysis pipelines, whereby specialists examine images as they normally would with the exception that the images appear in rank order according to a simple real-valued score. Promising results are shown for 319 112 images associated with 150 structures solved by the Joint Center for Structural Genomics pipeline during the 2006–2007 year. Overall, the algorithm achieves a mean receiver opera­ting characteristic score of 0.919 and a 78% reduction in human effort per set when considering an absolute score cutoff for screening images, while incurring a loss of five out of 150 structures.

BackgroundThe development of a mobile telephone food record has the potential to ameliorate much of the burden associated with current methods of dietary assessment. When using the mobile telephone food record, respondents capture an image of their foods and beverages before and after eating. Methods of image analysis and volume estimation allow for automatic identification and volume estimation of foods. To obtain a suitable image, all foods and beverages and a fiducial marker must be included in the image. ObjectiveTo evaluate a defined set of skills among adolescents and adults when using the mobile telephone food record to capture images and to compare the perceptions and preferences between adults and adolescents regarding their use of the mobile telephone food record. MethodsWe recruited 135 volunteers (78 adolescents, 57 adults) to use the mobile telephone food record for one or two meals under controlled conditions. Volunteers received instruction for using the mobile telephone food record prior to their first meal, captured images of foods and beverages before and after eating, and participated in a feedback session. We used chi-square for comparisons of the set of skills, preferences, and perceptions between the adults and adolescents, and McNemar test for comparisons within the adolescents and adults. ResultsAdults were more likely than adolescents to include all foods and beverages in the before and after images, but both age groups had difficulty including the entire fiducial marker. Compared with adolescents, significantly more adults had to capture more than one image before (38% vs 58%, P = .03) and after (25% vs 50%, P = .008) meal session 1 to obtain a suitable image. Despite being less efficient when using the mobile telephone food record, adults were more likely than adolescents to perceive remembering to capture images as easy (P < .001). ConclusionsA majority of both age groups were able to follow the defined set of skills; however, adults were less efficient when using the mobile telephone food record. Additional interactive training will likely be necessary for all users to provide extra practice in capturing images before entering a free-living situation. These results will inform age-specific development of the mobile telephone food record that may translate to a more accurate method of dietary assessment.

Several authors have previously demonstrated that the number of the skin mucous cells of fish is affected by many stressors. In the present study, two experiments were conducted in order to examine the effects of two common environmental conditions on the morphology of skin of sea bass and particularly on the number and diameter of skin mucous cells. In the first experiment, two groups of sea bass (mean weight 155.6±10.3 g SD) were maintained in two different concentrations of nitrate, 100 and 700 ppm respectively, for 48 h, while a third group was used as control. In the second experiment, sea bass (initial mean weight 78.9±3.1 g SD) were divided into four groups and each group was maintained in a different level of oxygen for 9 weeks. The oxygen concentration in each group was: 3.6±0.2 ppm, 4.7±0.2 ppm, 6.2±0.2 ppm and 8.2±0.2 ppm. In both experiments the effects of the two environmental factors on the morphology of the fish skin were examined histologically and a software containing a visual basic script macro, allowing quantification of the skin mucous cells, was used to analyze the skin tissue sections. Concerning the overall morphology of the skin and the diameter of the skin mucous cells, no differences were noted in both experiments (P>0.05). It was demonstrated however, that fish maintained in the lowest oxygen level and fish maintained in the highest concentration of nitrate exhibited significantly increased number of mucous cells per skin area (mm2). There is evidence that the enumeration of the skin mucous cells of fish can be used to monitor stress in fish.

Purpose This paper suggests a new method for determining the sewing damage that occurs in single jersey fabrics based on the calculation of the needle hole area. This paper also aims to investigate the effects of material type, sewing parameters, and repeated washing cycles on sewing damage by using this method. Design/methodology/approach Six knitted fabrics, differing in structure and raw material, were produced. Samples were sewn using different sewing parameters, and they were subjected to ten washing cycles. Values of average needle hole area, an objective indicator of sewing damage, were calculated before and after repeated washing cycles using image analysis software and were evaluated statistically. Findings The results showed that the average needle hole area calculated via the image analysis software effectively estimates sewing damage as the results obtained were compatible with those stated in the literature. Furthermore, fabric type, sewing direction, sewing thread type, and needle size significantly affected the sewing damage. However, stitch density did not affect the sewing damage. When the effect of washing cycles was compared, it was seen that washing leads to an increase in sewing damage. Originality/value A review of the existing literature shows that no previous study has evaluated sewing damage using image analysis software. This study proposes a novel objective method to determine the sewing damage that occurs in knitted fabrics., Ege University Scientific Research Projects Coordination Unit [14-MUH-069], This study is supported by Ege University Scientific Research Projects Coordination Unit. Project Number: 14-MUH-069.