smujiang
Leveraging computational methods to reveal information in medical images for assisting disease diagnosis & treatment.
Mayo ClinicRochester,MN
Pinned Repositories
CalculateSUV
Matlab code for calculating SUV in PET images
CARN
Direct Automated Quantitative Measurement of Spine by Cascade Amplifier Regression Network with Manifold Regularization
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.
Cytomine_GetAnnotation
Pull annotations and the corrosponding image patches from a Cytomine server.
MxIF_DAPI_ref_QC
MxIF image quality checking
Re-stained_WSIs_Registration
Re-stained whole slide image alignment
TumorStromaReaction
Quantitatively evaluate tumor stroma reaction within ovarian cancers, and establish assocaitaions to prognosis, molecular signatures.
WSI2DICOM
Simple prototype of converting whole slide image (WSI) to multiframe DICOM images
WSIPenMarkingRemoval
Remove pen-marking annotations on whole slide images(WSIs) for data achiving.
WSITools
Tools for whole slide image (WSI) processing. Especially for (pairwise) patch extraction, annotation parsing and data preparation for deep learning purposes.
smujiang's Repositories
smujiang/CARN
Direct Automated Quantitative Measurement of Spine by Cascade Amplifier Regression Network with Manifold Regularization
smujiang/Cytomine_GetAnnotation
Pull annotations and the corrosponding image patches from a Cytomine server.
smujiang/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
smujiang/ObjectDetectionAPIGuide
A self summarized tutorial for Object detection API. https://github.com/tensorflow/models/tree/master/research/object_detection
smujiang/quip_cnn_segmentation
CNN based segmentation codes
smujiang/ALOCC_Keras
Keras implementation of Adversarially Learned One-Class Classifier or ALOCC for short.
smujiang/ASAP
Program for the analysis and visualization of whole-slide images in digital pathology
smujiang/clinical-grade-computational-pathology-using-weakly-supervised-deep-learning-on-whole-slide-images
首个临床级别的 AI 系统可用源码
smujiang/Conv-Autoencoder
Convolutional Autoencoder
smujiang/deep-visualization-toolbox
DeepVis Toolbox
smujiang/DigiPath_MLTK
smujiang/Fast_WSI_Color_Norm
Codes for Fast GPU-Enabled Color Normalization of Whole Slide Images in Digital Pathology
smujiang/keras-grad-cam
An implementation of Grad-CAM with keras
smujiang/keras_to_tensorflow
General code to convert a trained keras model into an inference tensorflow model
smujiang/Kernelized-Rank-Learning
Kernelized rank learning for personalized drug recommendation
smujiang/Mask_RCNN
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
smujiang/matterport-maskrcnn-with-tensorflow-serving
Custom Mask R-CNN matterport's model with tensorflow serving
smujiang/MIL-nature-medicine-2019
smujiang/models
Models and examples built with TensorFlow
smujiang/mrcnn_serving_ready
🛠 Converting Mask R-CNN Keras model to Tensorflow model and Serving model
smujiang/NCRF
Cancer metastasis detection with neural conditional random field (NCRF)
smujiang/nehe-opengl
The complete archive of all NeHe OpenGL Lessons available at http://nehe.gamedev.net.
smujiang/NucleiSegmentation
cGAN-based Multi Organ Nuclei Segmentation
smujiang/openseadragon
An open-source, web-based viewer for zoomable images, implemented in pure JavaScript.
smujiang/Pytorch-UNet
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
smujiang/salad
A toolbox for domain adaptation and semi-supervised learning. Contributions welcome.
smujiang/SuperCRF
smujiang/Thread-Portrait
Here is the code I used to make my Thread Portrait.
smujiang/USCIS-Case-Tracker
Check USCIS case status
smujiang/YNet
Y-Net: Joint Segmentation and Classification for Diagnosis of Breast Biopsy Images