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The fsleyes-widgets package contains a collection of GUI widgets and utilities, based on wxPython, which are used by fsleyes-props and FSLeyes.
This package provides the Python Client code for accessing neuroimaging templates hosted using TemplateFlow.
SDCFlows (Susceptibility Distortion Correction workFlows) is a Python library of NiPype-based workflows to preprocess B0 mapping data, estimate the corresponding fieldmap and finally correct for susceptibility distortions. Susceptibility-derived distortions are typically displayed by images acquired with EPI MR schemes.
Nipype provides a uniform interface to existing neuroimaging software and facilitates interaction between these packages within a single workflow. Nipype provides an environment that encourages interactive exploration of algorithms from different packages.
DIPY is the paragon 3D/4D+ medical imaging library in Python. It contains generic methods for spatial normalization, signal processing, machine learning, statistical analysis and visualization of medical images. Additionally, it contains specialized methods for computational anatomy including diffusion, perfusion and structural imaging.
This package provides processing pipelines for structural MRI.
niworkflows is capable of converting between formats and resampling images to apply transforms generated by the most popular neuroimaging packages and libraries (AFNI, FSL, FreeSurfer, ITK, and SPM).
CiftiLib is a C++ library for CIFTI-2 file reading/writing. It additionally supports CIFTI-1 files, and supports both on-disk and in-memory access. It also provides C++ code for reading and writing generic NIfTI-1 and NIfTI-2 files.
CIFTI (Connectivity Informatics Technology Initiative) standardizes file formats for the storage of connectivity data. These formats are developed by the Human Connectome Project and other interested parties.
See http://www.nitrc.org/projects/cifti/ for more information.
This package provides a Pydantic schema for BIDS Stats Models.
The indexed_gzip project is a Python extension which aims to provide a drop-in replacement for the built-in Python gzip.GzipFile class, the IndexedGzipFile. indexed_gzip was written to allow fast random access of compressed NIFTI image files (for which GZIP is the de-facto compression standard), but will work with any GZIP file.
This module provides simple, consistent access to package resources.
It helps developers working in continuous integration (CI) environments by providing essential information about the CI server. It can determine if the code is running on a CI server,identify the specific server,and detect if a pull request is being tested.
fMRIPrep is a fMRI data preprocessing pipeline that is designed to provide an easily accessible, state-of-the-art interface that is robust to variations in scan acquisition protocols and that requires minimal user input, while providing easily interpretable and comprehensive error and output reporting. It performs basic processing steps (coregistration, normalization, unwarping, noise component extraction, segmentation, skull-stripping, etc.) providing outputs that can be easily submitted to a variety of group level analyses, including task-based or resting-state fMRI, graph theory measures, and surface or volume-based statistics.
This package provides DICOM to NIfTI conversion with the added ability to extract and summarize meta data from the source DICOM files. The meta data can be injected it into a NIfTI header extension or written out as a JSON formatted text file.
Convert3d is a command-line tool for converting 3D images between common file formats. The tool also includes a growing list of commands for image manipulation, such as thresholding and resampling. The tool can also be used to obtain information about image files.
This package provides an implementation of TRX, a tractography file format designed to facilitate dataset exchange, interoperability, and state-of-the-art analyses, acting as a community-driven replacement for the myriad existing file formats.
seqeval is a Python framework for sequence labeling evaluation. seqeval can evaluate the performance of chunking tasks such as named-entity recognition, part-of-speech tagging, semantic role labeling and so on.
Modular, fast NLP framework, compatible with Pytorch and spaCy, offering tailored support for French clinical notes.
Quicksectx is a simple, fast and no-dependency Python implementation of interval search, adapted from the bx-python project.
This package provides a fast implementation of the Levenshtein distance with C++ and Cython.
The EDS-Pseudo project aims at detecting identifying entities in clinical documents, and was primarily tested on clinical reports at AP-HP's clinical data warehouse. The model is built on top of edsnlp, and consists in a hybrid model (rule-based + deep learning) for which we provide rules (eds-pseudo/pipes) and a training recipe. We also provide some fictitious templates and a script to generate a synthetic dataset.
This module can be used to extract or replace keywords in sentences, based on the FlashText algorithm.
Gensim is a Python library for topic modelling, document indexing and similarity retrieval with large corpora. Target audience is the NLP and IR communities.
This package provides a Python implementation of IAMsystem algorithm, a fast dictionary-based approach for semantic annotation, a.k.a entity linking.