Tools for computational pathology
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Kaapana is an open source toolkit for state of the art platform provisioning in the field of medical data analysis. The applications comprise AI-based workflows and federated learning scenarios with a focus on radiological and radiotherapeutic imaging. The name Kaapana comes from the Hawaiian word kaʻāpana, meaning "distributor" or "part".
PyTorch Connectomics: segmentation toolbox for EM connectomics
Read and write Neuroglancer datasets programmatically.
Nellie: Automated organelle segmentation, tracking, and hierarchical feature extraction in 2D/3D live-cell microscopy
Gaussian processes and Bayesian optimization for images and hyperspectral data
HistoClean is a tool for the preprocessing and augmentation of images used in deep learning models. This easy to use application brings together the most popular image processing packages from across the python universe, meaning no more looking at documentation! HistoClean provides real time feedback to augmentations and preprocessing options. This allows users to evaluate their steps before implementation.
Lattice light-sheet post-processing utility.
An interactive image processing program for biologists written in Python.
Accurate segmentation of bacterial microscope images using deep learning synthetically generated image data.
A python package to analyze the matrix fiber orientation and intensity around cells in fiber matrices (as a proxy for cellular forces).