Approach that won 3rd place in the OCELOT 2023 Challenge. Multi-organ H&E-based deep learning model for cell detection, applicable for tumor cellularity/ purity/ content estimation.
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Updated
Jun 6, 2024 - Python
Approach that won 3rd place in the OCELOT 2023 Challenge. Multi-organ H&E-based deep learning model for cell detection, applicable for tumor cellularity/ purity/ content estimation.
Awesome List of Digital and Computational Pathology Resources
This repo provides an exhaustive pipeline of processing TCGA whole-slide images for downstream multiple instance learning.
Official implementation of "ASF-YOLO: A Novel YOLO Model with Attentional Scale Sequence Fusion for Cell Instance Segmentation".
Code for the paper " PDL: Regularizing Multiple Instance Learning with Progressive Dropout Layers "
A Python package for handling histopathology whole-slide images using multiple instance learning (MIL) techniques.
Repository for "Integrative Graph-Transformer Framework for Histopathology Whole Slide Image Representation and Classification""
Package using StarDist and Python that performs object detection and spatial analysis on H&E images
SOPHYSM - SOlid tumors PHYlogenetic Spatial Modeller - Julia GUI for Histological Analysis and Cancer Simulation
[MedIA2023 & MICCAI2022 ] Ambiguity-aware breast tumor cellularity estimation via self-ensemble label distribution learning
PAMA: Position-aware masked autoencoder for histopathology WSI representation learning
Implementation of MultiStain-CycleGAN
DL-model for multi-class tissue segmentation in colorectal cancer H&E slides, developed as part of the SemiCOL2023 Challenge.
Project title: Using Deep Learning to predict overall survival times for breast cancer from H&E whole slide biopsy
KBSMC colon cancer grading dataset repository
In this project, we perform exploratory analysis on the data and try out different models to give the best results.
tessellating tumor area in whole slide images into square tiles
The code for LAGE-Net
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