Neuron Tracing Vaa3D (MST)

Description

3D Neuron Tracing using Dockerized version of Vaa3D Minimum Spanning Tree (MST).

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Neuron Tracing Vaa3D (App2)

Description

Vaa3d All-Path-Pruning 2.0 (APP2) dockerised workflow for BIAFLOWS.

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Object Tracking (MU-Lux-CZ)

Description

Cell tracking using MU-Lux-CZ algorithm. Dockerized Workflow for BIAFLOWS implemented by Martin Maska (Masaryk University).

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Object Tracking (Octave)

Description

Nuclei tracking in 2D time-lapse with Octave tracker (adapted from Matlab LOBSTER version.

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Object Tracking (ImageJ)

Description

Object tracking. For each time-frame, an image mask is obtained from median filtering (user defined radius), thresholding (user defined level) and hole filling. Convex objects are split apart by distance map watershed from regional intensity maxima (user defined noise tolerance), eroded (user defined radius) and analyzed as 3D particles (assuming some overlap between objects from a frame to the next frame). Finally, division events are analyzed and accounted for to relabel objects.

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Nuclei Tracking (TrackMate)

Description

Track non-dividing particles in 2D time-lapse image.

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Nuclei Segmentation 3D (Ilastik)

Description

Execute Nuclei Segmentation in 3D images using pixel classification with ilastik.

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Nuclei Segmentation (U-Net)

Description

U-Net segmentation as presented in Reference Publication. The model predicts three classes: background, edge and foreground. The model was trained with Kaggle Data Science Bowl (DSB) 2018 training set.

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Nuclei Segmentation (DeepCell)

Description

Nuclei Segmentation using Deep Learning for single cell analysis (DeepCell).

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Spot Detection 3D Hessian (ImageJ)

Description

3D spot detection using the Determinant of Hessian (DoH) and the detection of 3D minima.

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