This workflow trains MSET landmark detection models from a dataset of annotated images.
This is a (Cython-based) Python wrapper for Philipp Krähenbühl's Fully-Connected CRFs (version 2).
PyTorch is an open-source machine learning library for Python, based on Torch, used for applications such as natural language processing.
This workflow segments glands from H&E stained histopathological images from the Gland Segmentation Challenge (GlaS2015) using deep learning (UNet). UNet implementation largely inspired from PyTorch-UNet by Milesial.
ImageJ/FIJI plugin generating contour lines with equal spacing on top of an image (using overlay).
