There are 20 repositories under medical-image-computing topic.
AI Toolkit for Healthcare Imaging
The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.
:warning: OBSOLETE | Multi-platform, free open source software for visualization and image computing.
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 were used to develop and evaluate the performance of the proposed method.
Dicoogle - Open Source PACS
Detecting Pneumonia in Chest X-ray Images using Convolutional Neural Network and Pretrained Models
[MICCAI'24] Official implementation of "BGF-YOLO: Enhanced YOLOv8 with Multiscale Attentional Feature Fusion for Brain Tumor Detection".
[MICCAI'23] Official implementation of "RCS-YOLO: A Fast and High-Accuracy Object Detector for Brain Tumor Detection".
Diffusion MRI analysis and visualization in 3D Slicer open source medical imaging platform.
[IMAVIS] Official implementation of "ASF-YOLO: A Novel YOLO Model with Attentional Scale Sequence Fusion for Cell Instance Segmentation".
A collection of deep learning models with a unified API.
Slicer extensions index
Code for analyzing medical images saved as .dicom files
[ICIP'24 Lecture Presentation] Official implementation of "CST-YOLO: A Novel Method for Blood Cell Detection Based on Improved YOLOv7 and CNN-Swin Transformer".
A qt-based 3D data visualization tool.
Template to be used as a starting point for creating a custom 3D Slicer application
Constrained Large Deformation Diffeomorphic Image Registration (CLAIRE)
Code for Paper: Multi Scale Curriculum CNN for Context-Aware Breast MRI Malignancy Classification
PyTorch implementation of Grouped SSD (GSSD) and GSSD++ for focal liver lesion detection from multi-phase CT images (MICCAI 2018, IEEE TETCI 2021)
Paper notes in deep learning/machine learning and computer vision
[MICCAI 2022 Best Paper Finalist] Bayesian Pseudo Labels: Expectation Maximization for Robust and Efficient Semi Supervised Segmentation
The easiest tool for experimenting with radiomics features.
Cancer Detection from Microscopic Images by Fine-tuning Pre-trained Models ("Inception") for new class labels
A jupyter widget for the cornerstone library to make showing flashy images with nice tools easier.
Segmentation-based measurements with DICOM import and export of the results.