Open source tools for computational pathology - Nature BME

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

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.

Computationally efficient multi-scale foundation model for computational pathology. 71M parameters, runs end-to-end on a single consumer GPU.

Pathology foundation models as well as ViT MIL models will be finetuned & benchmarked at the HPC server with Graphcore's IPUs. This service has been provided by AICA, a national data center agency for the support of high performance computing(HPC), located in Gwangju, s. Korea.