Data-efficient and weakly supervised computational pathology on whole slide images - Nature Biomedical Engineering

Cancer metastasis detection with neural conditional random field (NCRF)

Attention-Challenging Multiple Instance Learning for Whole Slide Image Classification (ECCV2024)

Official code for "Self-Supervised driven Consistency Training for Annotation Efficient Histopathology Image Analysis" Published in Medical Image Analysis (MedIA) Journal, Oct, 2021.

PFA-ScanNet: Pyramidal Feature Aggregation With Synergistic Learning for Breast Cancer Metastasis Analysis (Architecture Only Pytorch Implementation).

The implementation of our pricai18 paper "Multiple Visual Fields Cascaded Convolutional Neural Network for Breast Cancer Detection."

Image Processing and CV on Whole Slide Images

AEM: Attention Entropy Maximization for Multiple Instance Learning based Whole Slide Image Classification

Dissertation completed for the award of MSci in Computer Science. This dissertation is about automated breast cancer detection in low-resolution whole-slide pathology images using a deep convolutional neural network pipeline.