The napari-pyclesperanto-assistant is a yet experimental napari plugin for building GPU-accelerated image processing workflows targeting life-sciences and bio-image analysis. It is part of the clEsperanto project. It uses pyclesperanto and pyopencl as backend for processing images.

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

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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 )


Human colon tissue

Submitted by Perrine on Mon, 08/26/2019 - 11:30

One of the principal challenges in counting or segmenting cells or cell nuclei is dealing with clustered objects such as in tissues. To help assess algorithms' performance in this regard, synthetic 3D image sets of human colon tissue are provided in two diferent levels of quality: high SNR and low SNR. Ground truth is available as well.