Medical Image Analysis library for Python
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Updated
Feb 25, 2019 - Python
Medical Image Analysis library for Python
Assignments for the Course CS 736: Medical Image Computing. IIT Bombay
This is a small package for 3D slicer fiducial manipulation and analysis.
An open source algorithm to generate a 3D model of the women bra. This allows ONEBra to build personalized/customized cups for symmetric breast restoration starting from a simple 3D photo.
Simple Linear Iterative Clustering adapted for 4D DCE-MRI or other perfusion imaging
Unofficial implementation for ScanNet (a fast WSI prediction method) in PyTorch.
[MICCAI 2022 Best Paper Finalist] Bayesian Pseudo Labels: Expectation Maximization for Robust and Efficient Semi Supervised Segmentation
Official implementation of "ASF-YOLO: A Novel YOLO Model with Attentional Scale Sequence Fusion for Cell Instance Segmentation".
A jupyter widget for the cornerstone library to make showing flashy images with nice tools easier.
Computational Biophysics for Medicine in 3D Slicer
[STACOM-MICCAI 2019] Deep Learning Registration for Cardiac Motion Tracking
Code, data and model for Pérez-García et al. 2021, "A self-supervised learning strategy for postoperative brain cavity segmentation simulating resections"
Biomedical Visualization and Analysis Framework
3D Slicer module that creates a gradient map representing the bone thickness of a volume using VTK ray-casting.
The easiest tool for experimenting with radiomics features.
A qt-based 3D data visualization tool.
PyTorch implementation of Grouped SSD (GSSD) and GSSD++ for focal liver lesion detection from multi-phase CT images (MICCAI 2018, IEEE TETCI 2021)
Official implementation of "CST-YOLO: A Novel Method for Blood Cell Detection Based on Improved YOLOv7 and CNN-Swin Transformer".
A collection of deep learning models with a unified API.
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