Yapic

Description

Yet another pixel classifier Yapic is a deep learning tool to :

train your own filter to enhance the structure of your choice 

train multiple filter at once 

it is based on the u-net convolutional filter . 

To train it : annotation can come from example from Ilastik software , tif labelled files can be transferred to yapic. 

Training takes about hours to days , prediction takes seconds once trained .

It can be ran from command line .

note that only 10 to 20 images with sparse labeling are required for efficient training 

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QuPath

Description

QuPath is open source software for Quantitative Pathology. QuPath has been developed as a research tool at Queen's University Belfast.

QuPath

Pyxit Landmark detection

Description

It is a trainable interest point (anatomical landmarks) detection algorithm. It requires images and interest point coordinates. It can run independantly (using csv files to describe coordinates) or it can be executed using Cytomine.

 

Typical application: Morphometric studies (e.g. in zebrafish/drosphila development)

 

Used in: Evaluation and Comparison of Anatomical Landmark Detection Methods for Cephalometric X-Ray Images: A Grand Challenge http://dx.doi.org/10.1109/TMI.2015.2412951 Automatic localization of interest points in zebrafish images with tree-based methods 

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Landmark detection example

ilastik - Automatic Tracking

Description

Fully-automated cell tracking of 2D+time or 3D+time images with some parameter tuning

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ClassifyPixels (CellProfiler)

Description

not available in version 3.0 and up?

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