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Jun Jiang's Projects

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电子图书

adversarial-learning-of-cancer-tissue-representations icon adversarial-learning-of-cancer-tissue-representations

Corresponding code of 'Quiros, A. C., Coudray, N., Yeaton, A., Sunhem, W., Murray-Smith, R., Tsirigos, A., Yuan, K. Adversarial learning of cancer tissue representations. The 24th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2021'

alocc_keras icon alocc_keras

Keras implementation of Adversarially Learned One-Class Classifier or ALOCC for short.

asap icon asap

Program for the analysis and visualization of whole-slide images in digital pathology

carn icon carn

Direct Automated Quantitative Measurement of Spine by Cascade Amplifier Regression Network with Manifold Regularization

cellularcomposition icon cellularcomposition

Interactive modules to digitally annotate H&E whole slide images, construct cell and tissue level features and classify cell types. Specifically for a case study of differentiating borderline and high-grade serous ovarian tumors.

cornerstone icon cornerstone

JavaScript library to display interactive medical images including but not limited to DICOM

cytomine_python_client-0.1.4_for_python_3.6 icon cytomine_python_client-0.1.4_for_python_3.6

This is a installation package of Cytomine_Python_Client-0.1.4 for python 3.6. The original one is just compatible with python 2.7, which can be cloned from https://github.com/cytomine/Cytomine-python-client

drugcell icon drugcell

A visible neural network model for drug response prediction

fast_wsi_color_norm icon fast_wsi_color_norm

Codes for Fast GPU-Enabled Color Normalization of Whole Slide Images in Digital Pathology

fftw3 icon fftw3

This is the official repository for the FFTW Fourier transform library, version 3.x

gwnet icon gwnet

802.1x linux client for southern medical university

hipt icon hipt

Hierarchical Image Pyramid Transformer - CVPR 2022 (Oral)

histovae icon histovae

This repository contains work towards HistoVAE: creating meaningful representations of Histopathology images using Variational Autoencoders.

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