YeastSpotter

Description

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.

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MSRC Registration Toolbox

Description

This python toolbox performs registration between 2-D microscopy images from the same tissue section or serial sections in several ways to achieve imaging mass spectrometry (IMS) experimental goals.

This code supports the following works and enables others to perform the workflows outlined in the following works, please cite them if you use this toolbox:

  • Advanced Registration and Analysis of MALDI Imaging Mass Spectrometry Measurements through Autofluorescence Microscopy10.1021/acs.analchem.8b02884

  • Next Generation Histology-directed Imaging Mass Spectrometry Driven by Autofluorescence Microscopy10.1021/acs.analchem.8b02885

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Nuclei Segmentation (ilastik)

Description

NEUBIAS-WG5 workflow for nuclei segmentation using ilastik v1.3.2 and Python post-processing.

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Mask-RCNN

Description

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.

Nuclei Segmentation (Mask-RCNN)

Description

NEUBIAS-WG5 workflow for nuclei segmentation using Mask-RCNN. The workflow uses Matterport Mask-RCNN. Keras implementation. The model was trained with Kaggle 2018 Data Science Bowl images.

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Landmark detection DMBL model prediction

Description

This workflow predict landmark positions on images by using DMBL landmark detection models.

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sumproduct

Description

An implementation of Belief Propagation for factor graphs, also known as the sum-product algorithm

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Landmark detection DMBL model training

Description

This workflow trains DMBL landmark detection models from a dataset of annotated images.

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Landmark detection LC models prediction

Description

This workflow predict landmark positions on images by using LC landmark detection models.

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Landmark detection LC models training

Description

This workflow trains LC landmark detection models from a dataset of annotated images.

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