Pinned Repositories
whole-slide-cnn
This repository provides scripts to reproduce the results in the paper "An annotation-free whole-slide training approach to pathological classification of lung cancer types by deep learning".
tensorflow-huge-model-support
This library is designed to speed up huge model training on unified memory.
hms2
Another annotation-free whole-slide training approach to pathological classification. This repository provides scripts to reproduce the results in the paper "Deep neural network trained on gigapixel images improves lymph node metastasis detection in clinical settings", including model training, inference, visualization, etc.
stain-mixup
The repository provide augment function of "Stain mix-up: Unsupervised domain generalization for histopathology images"
Pypi-Project-Template
hema_cell_dc
hp-gastritis-hms2-auxiliary
This project reproduces the results in the paper, 'A two-tiered deep learning-based model for histologic diagnosis of Helicobacter gastritis'.
aetherAI's Repositories
aetherAI/hp-gastritis-hms2-auxiliary
This project reproduces the results in the paper, 'A two-tiered deep learning-based model for histologic diagnosis of Helicobacter gastritis'.
aetherAI/hema_cell_dc
aetherAI/Pypi-Project-Template
aetherAI/hms2
Another annotation-free whole-slide training approach to pathological classification. This repository provides scripts to reproduce the results in the paper "Deep neural network trained on gigapixel images improves lymph node metastasis detection in clinical settings", including model training, inference, visualization, etc.
aetherAI/stain-mixup
The repository provide augment function of "Stain mix-up: Unsupervised domain generalization for histopathology images"
aetherAI/whole-slide-cnn
This repository provides scripts to reproduce the results in the paper "An annotation-free whole-slide training approach to pathological classification of lung cancer types by deep learning".
aetherAI/tensorflow-huge-model-support
This library is designed to speed up huge model training on unified memory.