Reverse Dependencies of SimpleITK

The following projects have a declared dependency on SimpleITK:

• fuse-med-ml — A python framework accelerating ML based discovery in the medical field by encouraging code reuse. Batteries included :)
• fw-gear-rtstruct-to-nifti — Flywheel Gear for converting RTStruct ROIs to NIfTI
• gandlf — PyTorch-based framework that handles segmentation/regression/classification using various DL architectures for medical imaging.
• ganondorf — A Gan Medical Image Learning Framework
• ganslate — GAN image-to-image translation framework made simple and extensible.
• gcam — An easy to use framework that makes model predictions more interpretable for humans.
• harp-image-preprocess — Cross-platform application for automating the processing of μCT and OPT image data.
• HD-GLIO — Tool for brain tumor segmentation. This is the result of a joint project between the Department of Neuroradiology at the Heidelberg University Hospital and the Division of Medical Image Computing at the German Cancer Research Center (DKFZ). See readme.md for more information
• headctools — A set of tools for preproccessing and performing brain segmentation and skull reconstruction on head CT images
• henmedlib — Package encapsulating all functions I used during my PhD.
• hesperos — A plugin to manually or semi-automatically segment medical data and correct previous segmentation data.
• hf-deepali — Image, point set, and surface registration library for PyTorch.
• hi-ml-cpath — Microsoft Health Futures package for deep learning on histopathology images
• hi-ml-multimodal — Microsoft Health Futures package to work with multi-modal health data
• highresnet — PyTorch implementation of HighRes3DNet
• Hive-MAIA — Python Package to support Deep Learning data preparation, pre-processing. training, result visualization and model deployment across different frameworks (nnUNet, nnDetection, MONAI).
• Hive-ML — Python package to run Machine Learning Experiments, within the Hive Framework.
• iblapps — IBL Applications
• Icube-radiomics — Perform Radiomics Feature Extraction and Machine Learning
• ifree — i love freedom, free my hand.
• imaxt-registration-tools — Image registration tools for IMAXT
• imdm — Data models for MRI and image applications
• imvis — Interactive visualization and processing of 3D medical images in python
• informatics — Framework of fast implementation data processing and operating pipelines
• ingradient-lib — Medical Deep Learning Framework
• ingradient-lib-temp — Medical Deep Learning Framework.
• ingradient-lib-temp2 — Medical Deep Learning Framework.
• ingradient-library-temp — Medical Deep Learning Framework
• Ingress2QSIRecon — Tool to ingress data from other pipelines for use in QSIRecon
• intensity-normalization — normalize the intensities of various MR image modalities
• interactivenet — InteractiveNet, a framework for minimally interactive medical image segmentation.
• ismi-utils — ISMI Utilities
• ITHscore — package for calculating ITHscore from CT image
• jrImgTools — Image utility functions for personal use
• jxImgTools — Image utility functions for personal use
• kagglerecipes — Useful code for different Kaggle competitions. Currently covering RSNA-MICCAI Brain Tumor Radiogenomic Classification Kaggle competition.
• karawun — DICOM image, segmgmentation image and fibre object converter
• LabelFusion — Label fusion strategies for multi-class labels.
• lama-phenotype-detection — Phenotype detection pipeline for finding abnormalities in mouse embryos
• lazybids — lazybids is a python package that helps interact with existing bids datasets and convert existing dicom or nifti datasets to BIDS.
• lesion-metrics — metrics for evaluating lesion segmentations
• linumpy — linumpy: microscopy tools and utilities
• liom-toolkit — Package to support the research of LIOM.
• lionz — A toolkit for precise segmentation of tumors in PET/CT scans.
• lsfm-fuse — A fusion algorithm in LSFM
• lsfmpy — HDF5-based software for storing and managing voluminous 3D imaging data
• lungmask — Package for automated lung segmentation in CT
• macapype — Pipeline for anatomic processing for macaque
• magellanmapper — 3D atlas analysis and annotation
• mdatpy — A pypi release of the MDAT
• med-dataloader — A general-purpose Dataloader for Tensorflow 2.x. It supports many medical image formats.
• med-imagetools — Med-Imagetools: Transparent and Reproducible Medical Image Processing Pipelines in Python
• medcam — An easy to use library that makes model predictions more interpretable for humans.
• MedicalImageConverter — Reads in medical images and structures them into 3D arrays with associated ROI/POIs if they exist.
• medimage-pkg — MEDimage is a Python package for processing and extracting features from medical images
• Medimgpy — A friendly Medical Image Processing Library using Python.
• medpicpy — A package to simplify loading medical imaging datasets.
• medsegpy — MedSegPy is a framework for research on medical image segmentation.
• MedShapeNetCore — MedShapeNetCore: A Lightweight 3D Repository for Computer Vision and Machine Learning
• medvision — A python library for medical image computer vision.
• medviz — Medical Image Visualization Tool 🐍🚀🎉🦕
• medvol — A wrapper for loading medical 3D image volumes such as NIFTI or NRRD images.
• membrain-seg — membrane segmentation in 3D for cryo-ET
• MemCNN — A PyTorch framework for developing memory efficient deep invertible networks.
• MIA-Tools — Medical Image Analysis Tools
• micg — Medical Image Changer
• micomputing — 'micomputing' is a package for medical image computing.
• MIDP — Medical Image Development Packages
• miplib — A Python software library for (optical) microscopy image restoration, reconstruction and analysis.
• mircat-stats — Mirshahi CT Analysis Toolkit (MirCAT), stats and dicom conversion only. Convert and Quantify CT NIfTI files.
• mircato — Add your description here
• mircato-stats — Statistics only version of MirCATo for CT image analysis. Much smaller build without torch.
• miscnn — Framework for Medical Image Segmentation with Convolutional Neural Networks and Deep Learning
• mist-medical — MIST is a simple, fully automated framework for 3D medical imaging segmentation.
• moosez — An AI-inference engine for 3D clinical and preclinical whole-body segmentation tasks
• mousechd — Segmenting hearts and screening congenital heart diseases in mice
• mrftools — Tools for Magnetic Resonance Fingerprinting
• mskt — vtk helper tools/functions for musculoskeletal analyses
• multiplex2brightfield — A package to convert a multiplex image to a virtual blightfield image such as H&E or IHC. Both the input and output are in OME-TIFF file format.
• napari-imsmicrolink — Plugin to perform IMS to microscopy registration using laser ablation marks.
• napari-medical-image-formats — A Plugin in order to read medical image formats such as DICOM and NIfTI
• napari-nD-annotator — A toolbox for annotating objects one by one in nD
• napari-simpleitk-image-processing — Process and analyze images using SimpleITK in napari
• napari-stpt — napari viewer which can read stpt, axio and imc images as zarr files
• ndreg — Registration package that does affine and LDDMM registration
• nekton — A python package for DICOM to NifTi and NifTi to DICOM-SEG and GSPS conversion
• NeuroRuler — A program that calculates head circumference from MRI data (.nii, .nii.gz, .nrrd).
• nifti2dicom — A package to convert NIfTI images to DICOM format using a reference DICOM series.
• niftiprocessing — A nifti processing tool
• NiftiResampler — Tools for reading dicom files, RT structures, and dose files, as well as tools for converting numpy prediction masks back to an RT structure
• nnunet — nnU-Net. Framework for out-of-the box biomedical image segmentation.
• nnunet-customized — nnU-Net. Framework for out-of-the box biomedical image segmentation.
• nnunet-inference-on-cpu-and-gpu — nnU-Net. Framework for out-of-the box biomedical image segmentation. Can do inference on both gpu(if cuda available) and cpu(if cuda not available)
• nnunetv2 — nnU-Net is a framework for out-of-the box image segmentation.
• nnunetv2-bm-custom — nnU-Net is a framework for out-of-the box image segmentation.
• ocelotz — OCELOT: diffeOmorphiC rEgistration for voxel-wise anOmaly Tracking - a tool to generate cohort specific normative PET/CT images.
• opencxr — a collection of algorithms for processing of chest radiograph (CXR) images
• opengate — Simulation for Medical Physics
• opentps-gui — Open source TPS for advanced proton therapy
• openwholeslide — Wrapper around tifffile library to have the same API as OpenSlide.