Code for the paper " PDL: Regularizing Multiple Instance Learning with Progressive Dropout Layers "

[IMAVIS] Official implementation of "ASF-YOLO: A Novel YOLO Model with Attentional Scale Sequence Fusion for Cell Instance Segmentation".

This repo provides an exhaustive pipeline of processing TCGA whole-slide images for downstream multiple instance learning.

A Python package for handling histopathology whole-slide images using multiple instance learning (MIL) techniques.

[MedIA2023 & MICCAI2022 ] Ambiguity-aware breast tumor cellularity estimation via self-ensemble label distribution learning

KBSMC colon cancer grading dataset repository

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.

The code for LAGE-Net

Implementation of MultiStain-CycleGAN

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.

Package using StarDist and Python that performs object detection and spatial analysis on H&E images

Awesome List of Digital and Computational Pathology Resources

Developed a fine-tuned EfficientNetB0 model which is a pre-trained Convolutional Neural Network (CNN) model to train using lungs and colon cancer dataset and classify if the unseen image belonged to benign, adenocarcinoma or squamous cell carcinoma cancer type.

Repository for "Integrative Graph-Transformer Framework for Histopathology Whole Slide Image Representation and Classification""

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

tessellating tumor area in whole slide images into square tiles