DeepCell

Description

 

DeepCell is neural network library for single cell analysis, written in Python and built using TensorFlow and Keras.

DeepCell aids in biological analysis by automatically segmenting and classifying cells in optical microscopy images. This framework consumes raw images and provides uniquely annotated files as an output.

The jupyter session in the read docs are broken, but the one from the GitHub are functional (see usage example )

deepcell

DragonFly

Description

Dragonfly is a software platform for the intuitive inspection of multi-scale multi-modality image data. Its user-friendly experience translates into powerful quantitative findings with high-impact visuals, driven by nuanced easy-to-learn controls.

For segmentation: It provides an engine fior machine Learning, Watershed and superpixel methods, support histological data .

It offers a 3D viewer, and python scripting capacities .

It is free for reserach use, but not for commercial usage.

DragonFly

FPBioimage

Description

FPBioimage is a volumetric visualization tool which runs in all modern web browsers. Try the tool yourself at our example site here.

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Image Data Explorer

Description

The Image Data Explorer is a Shiny app that allows the interactive visualization of images and ROIs associated with data points shown in a scatter plot. It is useful for exploring the relationships between images/ROIs and associated data represented in tabular format.

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EvaluateSegmentation Tool

Description

A command line tool that allows to quantitatively compare two volumes of binary segmentations. Implements 22 different metrics for comparing segmentations such as Dice Coefficient, Hausdorff Distance and average Distance. 

Automated workflow for parallel Multiview Reconstruction

Description

Automated workflow for performing multiview reconstruction of large multiview, multichannel, multiillumination time-lapse SPIM data on a high performance computing (HPC) cluster or on a single workstation. 

VascuSynth

Description

VascuSynth is an ITK-based synthetic image generator. It synthesizes volumetric images of vascular trees and generates a .gxl file of the ground-truth tree structure. VascuSynth receives a number of .txt configuration files and is capable of generating both ground truth ('ideal') images and images with added noise. The user is capable of choosing from a set simple noise additions and artefacts.

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Nuclei Tracking (ImageJ)

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3D Fill holes (mcib3d)

Description

Runs fill holes operation on 3D images.

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Maximum (3D) VIB Protocol

Description

This component convolves the image with maximum filter. Each voxel is set to the maximum value of its neighborhood. The neighborhood is defined by a kernel, which has a diameter of 3 voxels.

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