Highlights
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Register of deep learning-based products in radiotherapy
Book on MATLAB with Python 🐍
Streamline deep learning experiments using config files
Real-time Feature Pipelines in Python ⚡
Segment Anything in Medical Images
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
All Algorithms implemented in Python
This extension contains only a module with some tools to install PyTorch inside Slicer, using the best possible version.
SourceCode of serial tutorials on 3D Slicer extension development for beginners
Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog: mlengineer.io.
MetaPlanner is an open source automated treatment planning method that performs meta-optimization of treatment planning hyperparameters. It is meant for educational/research purposes and supports p…
A python module for scientific analysis of 3D data based on VTK and Numpy
Source code accompanying O'Reilly book: Machine Learning Design Patterns
Automated VMAT Planning [PMB'21, PMB'23]
Python-based Advanced Numerical Nonlinear Optimization for Radiotherapy
Semi Supervised Learning for Medical Image Segmentation, a collection of literature reviews and code implementations.
An awesome list of helpful resources for students learning MATLAB & Simulink. List includes tips & tricks, tutorials, videos, cheat sheets, and opportunities to learn MATLAB & Simulink.
Opensource Python project for cancer radiation treatment planning [AAPM'23]
The simplest, fastest repository for training/finetuning medium-sized GPTs.
Processing Library and Analysis Toolkit for Medical Imaging in Python
Slicer3D extension for rating using Likert-type score Deep-learning generated segmentations, with segment editor functionality. Created to speed up the validation process done by a clinician - the …
PyRaDiSe: A Python package for DICOM-RT-based auto-segmentation pipeline construction and DICOM-RT data conversion
Code related to Chapter 15 of the book; The evaluation of auto-contouring for radiotherapy
AICONSlab's DL benchmarking platform to OOD data in MRI
This repository contains data readers and examples for the three tracks of the Shifts Dataset and the Shifts Challenge.