Code for the paper " PDL: Regularizing Multiple Instance Learning with Progressive Dropout Layers "
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Updated
May 24, 2024 - Python
Code for the paper " PDL: Regularizing Multiple Instance Learning with Progressive Dropout Layers "
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".
[MedIA2023 & MICCAI2022 ] Ambiguity-aware breast tumor cellularity estimation via self-ensemble label distribution learning
A Python package for handling histopathology whole-slide images using multiple instance learning (MIL) techniques.
The code for LAGE-Net
In this project, we perform exploratory analysis on the data and try out different models to give the best results.
DL-model for multi-class tissue segmentation in colorectal cancer H&E slides, developed as part of the SemiCOL2023 Challenge.
SOPHYSM - SOlid tumors PHYlogenetic Spatial Modeller - Julia GUI for Histological Analysis and Cancer Simulation
Project title: Using Deep Learning to predict overall survival times for breast cancer from H&E whole slide biopsy
Package using StarDist and Python that performs object detection and spatial analysis on H&E images
Repository for "Integrative Graph-Transformer Framework for Histopathology Whole Slide Image Representation and Classification""
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
tessellating tumor area in whole slide images into square tiles
PAMA: Position-aware masked autoencoder for histopathology WSI representation learning
KBSMC colon cancer grading dataset repository
Implementation of MultiStain-CycleGAN
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