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Retrieves diverse shortest paths between two end-points. DiversePathsJ returns paths that can then be swiftly browsed and displayed on the image using the arrow keyboard keys, or exported in generic formats for further processing. It allows users to analyze multiple instances of the same objects exhibiting slight variations without the need for fine-tuning of the cost function. This tool is not restricted to quantitative estimation of shape features such as length and bending. It covers every problem in which a path is to be searched between two end-points.
Root analyzer
Serves for batch processing of large series of images. Root analyzer is designed for extracting and analyzing anatomical traits from root-cross section images. It uses basic knowledge about root morphology, such as cell and tissue size and locations. It lends the program to applications on a range of species. It segments the plant root from the image's background, classifies and characterizes the cortex, stele, endodermis and metaxylem, and produces statistics about the morphological properties of the root cells and tissues.
GRAPHIE / GRAPh based Histology Image Explorer
Allows users to explore, annotate and discover potential relationships in histology image collections. GRAPHIE is a visual analytics tool designed to assist pathologists and systems biology researchers It discovers, annotates and reveals potential relationships of phenotypical properties within a biologically relevant context. This tool uses the bag-of-features (BoFs) approach to capture visual patterns from a given collection of histology images, and thus allowing a semantic organization of unstructured image collections.
Automating Morphological Profiling with Generic Deep Convolutional Networks
Uses deep feature transfer for generating morphological profiles without human interaction. Automating Morphological Profiling with Generic Deep Convolutional Networks achieves higher accuracies than previous classical methods, needs less time and expertise to extract profiles and allows for true automated high content screening by taking the human out of the loop. Furthermore, it enables fully automated processing of microscopy images without need for single cell identification.
SMASH / Semi-automatic Muscle Analysis using Segmentation of Histology
Provides an automatic and standardized image segmentation platform. SMASH permits users to measure multiple facets of muscle histology. It carries a high monetary cost and is not specifically designed for skeletal muscle analysis. This tool generates results validated against legacy methods showing largely consistent results between methods for fiber type and centrally nucleated fiber (CNF) percentages. It reduces the border region between adjacent fibers, it is also capable of delineating interstitial space between adjacent fibers when there is an appreciable separation.
Finds and simulates cell file in light microscopy images. Cefiler permits users to avoid supervised training and allows results quality quantification. It starts by identifying cells to individualize the cells in the image. Then, this tool recognizes and individualizes the alignments of anatomical structures. It finishes by storing anatomically and typing qualitatively the cell files. The method can be applied to any images with high contrast between the walls and lumens and a clear cellular organization.
EasyPCC / Easy Plant Canopy Coverage
Allows high-throughput measurements of plant canopy coverage ratios under field conditions. EasyPCC is a machine-learning-based tool that comprises two major components: (1) model generation through the acquisition of a training dataset from the raw images, and (2) the segmentation of the vegetation from the background of the image. The software contains functions including image sorting, user-defined decision-tree-based segmentation model (DTSM) generation, image processing, and plant canopy coverage ratio (PCCr) derivation.
IHC Toolbox / Immunohistochemistry Toolbox
Detects the basic components in an Immunohistochemistry (IHC) image. IHC Toolbox was developed using a semi-automatic scheme that is suitable for different kinds of IHC image analysis. The software includes functions for semi-automatic color selection, automatic statistical color detection, automatic nuclei segmentation and automatic gland detection. It allows users to save and transfer their created models and parameters to different users for the reproduction of detection results in different laboratories.
Automates image analysis of estrogen receptor (ER), progesterone receptor (PR), and Ki-67 tissue sections. ImmunoRatio uses monoclonal antibodis 6F11, PgR636 and MIB-1 to detect respectively ER, PR and Ki-67. It is able to make blank field correction thank to the utilization of the Calculator Plus plugin. The tool segments the DAB- and hematoxylin-stained nuclei areas from a microscope image, calculates the labeling index, and generates a pseudo-colored result image matching of the segmentation.
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