A command line tool that allows to quantitatively compare two volumes of binary segmentations. Implements 22 different metrics for comparing segmentations such as Dice Coefficient, Hausdorff Distance and average Distance.
Automated workflow for performing multiview reconstruction of large multiview, multichannel, multiillumination time-lapse SPIM data on a high performance computing (HPC) cluster or on a single workstation.
Code to segment yeast cells using a pre-trained mask-rcnn model. We've tested this with yeast cells imaged in fluorescent images and brightfield images, and gotten good results with both modalities. This code implements an user-friendly script that hides all of the messy implementation details and parameters. Simply put all of your images to be segmented into the same directory, and then plug and go.
This is an implementation of Mask R-CNN on Python 3, Keras, and TensorFlow. The model generates bounding boxes and segmentation masks for each instance of an object in the image. It's based on Feature Pyramid Network (FPN) and a ResNet101 backbone.