Stars
Pytorch pipeline for 3D image domain translation using Cycle-Generative-Adversarial-networks, without paired examples.
Code for the paper "Analysis and comparison of cycle-consistent adversarial networks for CBCT to CT translation for adaptive radiotherapy in cervical and lung cancer patients"
Unofficial implementation of "Paired cycle-GAN-based image correction for quantitative cone-beam computed tomography" published in Medical Physics.
An analysis on Ensemble Learning optimized Medical Image Classification with Deep Convolutional Neural Networks
Multi-Disease Detection in Retinal Imaging based on Ensembling Heterogeneous Deep Learning Models
a framework for Automated Classification of Medical Images
Public repo for the ICCV2021-CVAMD paper "Is it Time to Replace CNNs with Transformers for Medical Images?"
The implementation of the 3D-SW-UNet for brain tissue segmentation implemented in Tensorflow
nnDetection is a self-configuring framework for 3D (volumetric) medical object detection which can be applied to new data sets without manual intervention. It includes guides for 12 data sets that …
Pytorch、Scikit-learn实现多种分类方法，包括逻辑回归（Logistic Regression）、多层感知机（MLP）、支持向量机（SVM）、K近邻（KNN）、CNN、RNN，极简代码适合新手小白入门，附英文实验报告（ACM模板）
Deep-learning Radiomics for Classification Modelling
DREES (Dose response explorer system) is an in-house Matlab-based open source software customized for modeling and exploring dose response in radiation oncology.
Matlab/Octave based platform for Radiological Research.
A Slicer extension to provide a GUI around pyradiomics
Open-source python package for the extraction of Radiomics features from 2D and 3D images and binary masks. Support: https://discourse.slicer.org/c/community/radiomics