Discover PathologyDataScience/MuTILs_Panoptic Open Source project

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Language
Python
License
MIT License
Created over 1 year ago
Updated over 1 year ago

PathologyDataScience

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Amgad M, Salgado R, Cooper LA. A panoptic segmentation approach for tumor-infiltrating lymphocyte assessment: development of the MuTILs model and PanopTILs dataset. medRxiv 2022.01.08.22268814.

BCSS

Use this to download all elements of the BCSS dataset described in: Amgad M, Elfandy H, ..., Gutman DA, Cooper LAD. Structured crowdsourcing enables convolutional segmentation of histology images. Bioinformatics. 2019. doi: 10.1093/bioinformatics/btz083

Python

135

SurvivalNet

Deep learning survival models

Python

113

SCNN

Survival Convolutional Neural Networks

NuCLS

NuCLS: A scalable crowdsourcing, deep learning approach and dataset for nucleus classification, localization and segmentation

Jupyter Notebook

HistomicsML2

A tool for training machine-learning models with whole-slide imaging datasets

JavaScript

HistomicsML

An interactive machine learning framework for large histopathology images.

JavaScript

HiPS

Histomic Prognostic Signature (HiPS): A population-level computational histologic signature for invasive breast cancer prognosis

Python

MatDigitalPathology

Matlab functions to support analysis of digital pathology images.

MATLAB

MiscSurvivalUtils

Miscellaneous tools for data management and classical survival analysis.

Python

HistXtract

A pipeline for extracting nuclear morphometry features from whole-slide images.

MATLAB

IHC-Analysis

Jupyter Notebook

glimr

A simplified wrapper for hyperparameter search with Ray Tune.

Python

PathologyDataScience/MuTILs_Panoptic

PathologyDataScience

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