Reverse Dependencies of SimpleITK

The following projects have a declared dependency on SimpleITK:

• advanced-radiomics — Advanced Radiomics Functions.
• aics-tf-registration — Rigid registration algorithm for generating training/testing data for transfer function model
• aind-mri-targeting — Tools to plan and execute MRI-guided targeting experiments
• aind-mri-utils — MRI utilities library for aind teams.
• aind-registration-utils — Generated from aind-library-template
• allensdk — core libraries for the allensdk.
• amsaf — The HART Lab's tools for registration-based segmentation
• ardent — A tool for nonlinear image registration.
• armcrop — A machine learning model that crops CT scans to a bone of interest in the arm
• asltk — A quick to use library to process images for MRI Arterial Spin Labeling imaging protocols.
• aucmedi — AUCMEDI - a framework for Automated Classification of Medical Images
• auditapp — AUDIT, Analysis & evalUation Dashboard of artIficial inTelligence
• automatic-actions — Test lib for automatic actions.
• AutoParc — Automatic Brain Parcellation Tools
• autorad — Radiomics-related modules for extraction and experimenting
• autoslicer — An automated tool for medical image processing with DICOM to NIfTI conversion, segmentation, and analysis.
• AxCorSRMRI — no summary
• balaitous — Codebase to run the Balaitous model
• bigstream — Tools for distributed alignment of massive images
• bimcvcovid19i — Interface for working with BIMCV COVID 19 dataset
• bio-volumentations — Library for 3D-5D augmentations of volumetric multi-dimensional time-lapse biomedical images with annotations
• bioimageit — A FAIR data management and image analysis framework
• biom3d — Biom3d. Framework for easy-to-use biomedical image segmentation.
• bioxelnodes — no summary
• body-composition-analysis — A package for body composition analysis from DICOM images.
• body-organ-analysis — BOA is a tool for segmentation of CT scans developed by the SHIP-AI group at the Institute for Artificial Intelligence in Medicine (https://ship-ai.ikim.nrw/). Combining the TotalSegmentator and the Body Composition Analysis, this tool is capable of analyzing medical images and identifying the different structures within the human body, including bones, muscles, organs, and blood vessels.
• brainglobe-atlasapi — A lightweight python module to interact with and generate atlases for systems neuroscience.
• brainglobe-template-builder — Build unbiased anatomical templates from individual images
• BrainLes-HD-BET — TODO.
• BrainParc — Brain Parcellation Tools
• BraTS-Toolkit — BraTS Toolkit is a holistic approach to brain tumor segmentation allowing to build modular pipeliens for preprocessing, segmentation and fusion of segmentations.
• brickstudy — A package for analysis of MRI
• brkraw — Bruker PvDataset Loader
• bronchipy — Supporting tools for processing the output of the AirFlow pipeline.
• bruker — Bruker PvDataset Loader
• carde — Carbide Detection Tool
• CartiMorph-nnUnet — nnU-Net with minor revisions tailored for the CartiMorph framework.
• catopuma — Custom Advanced Tensorflow Objects to Preprocess, Upload, Model and Augment
• cell-locator-cli — CLI Tools for Cell Locator
• cellori — Cellori
• celltk — live-cell image analysis
• cerebrumscanner — Cerebrum Scanner Project
• chunky3d — A 3D array-like NumPy-based data structure for large sparsely-populated volumes
• CircuitSeeker — Tools for finding neural circuits
• cleanX — Python library for cleaning data in large datasets of Xrays
• CloudReg — Automatic terabyte-scale cross-modal brain volume registration
• collageradiomicscli — Get Collage features from an image and a binary mask
• convexAdam — Convex Adam
• cp-utils-hmv — tools to deal with images coming from cell profiler pipelines
• crappy — Command and Real-time Acquisition in Parallelized Python
• crashs — CRASHS: Cortical Reconstruction for Automated Segmentation of Hippocampal Subfields (ASHS)
• cryoemservices — Services for CryoEM processing
• CTHeadDeformation — Perform Realistic Head Deformations
• CTPreprocessing — First preprocessing on input dicoms
• ctunet — 3D UNet for CT segmentation with PyTorch
• cvasl — A package for analysis of MRI
• cxas — Segmentation of 159 anatomical classes for Chest X-Rays.
• cyto-studio — napari viewer which can read multiplex images as zarr files
• dacapo-ml — Framework for deployment of volumetric machine learning models, and easy composition of training jobs.
• dart-app — no summary
• dcmrtstruct2nii — Convert DICOM RT-Struct to nii
• dds4xnat — Renames the scan type for MR sessions stored on XNAT using the DeepDicomSort algorithm
• deep-medical-toolkit — Tools to facilitate deep learning research with a focus on medical imaging.
• DeepBrainSeg — Deep Learning tool for brain tumor segmentation.
• deepdefacer — Automatic Removal of Facial Features from MRI Images
• DeepMuon — Interdisciplinary Deep Learning Platform
• delia — DICOM Extraction for Large-scale Image Analysis (DELIA).
• delira — no summary
• dice-score-3d — Utility for calculating the Dice Similarity Coefficient (DSC) for 3D segmentation masks.
• dicom2stl — A script to extract an iso-surface from a DICOM series to produce an STL mesh.
• DicomRTTool — Services for reading dicom files, RT structures, and dose files, as well as tools for converting numpy prediction masks back to an RT structure
• dicomselect — no summary
• disptools — Generate displacement fields with known volume changes
• dorkylever-lama-phenotype-detection — Phenotype detection pipeline for finding abnormalities in mouse embryos
• dosma — An AI-powered open-source medical image analysis toolbox
• dpatk — The Dynamic PET Analysis Toolkit
• dsbundle — Streamline your data science setup with dsbundle in one effortless install.
• dti-conv — A command line utility that allows easy modifications on DWI volumes and Datasets.
• dti-pipeline — A command line utility that allows easy modifications on DWI volumes and Datasets.
• dwipy — DWI anaylysis pipeline
• echo-lv — Library for Echocardiographic images
• edanif — EDA-NIf creates a dataframe containing meta information of NIfTi files and provides several useful features.
• eisen-core — Eisen is a collection of tools to train neural networks for medical image analysis
• EIVideo — EIVideo - 交互式智能视频标注工具，几次鼠标点击即可解放双手，让视频标注更加轻松
• empanada-napari — Napari plugin of algorithms for Panoptic Segmentation of organelles in EM
• enhancez — no summary
• ereg — efficient, pythonic cross-platform image registrations
• escam-toolbox — Toolkit with radiomics utilities and UI compponents
• exodeepfinder — ExoDeepFinder is an original deep learning approach to localize macromolecules in cryo electron tomography images. The method is based on image segmentation using a 3D convolutional neural network.
• falconz — FalconZ: A streamlined Python package for PET motion correction.
• fhir-pyrate — FHIR-PYrate is a package that provides a high-level API to query FHIR Servers for bundles of resources and return the structured information as pandas DataFrames. It can also be used to filter resources using RegEx and SpaCy and download DICOM studies and series.
• FigureGenerator — Making screenshots for presentations and manuscripts.
• file-cache — Cache dataframe with local hd5 file, and reduce the memory by convert type for number
• FileConversionTool — A Python package for converting medical imaging files between different formats.
• fireants — FireANTs: Adaptive Riemannian Optimization for Multi-Scale Diffeomorphic Registration
• fish-reg — fish video registration software
• flexcalc — CT data pre- and post-processing tools, simulation of spectral data, and batch-processing of large number of datasets
• forger — A package for 3D image augmentation
• frd-score — Package for calculating Fréchet Radiomics Distance (FRD)
• fredtools — FRED tools is a collection of python functions for image manipulation and analysis. See more on https://github.com/jasqs/FREDtools.