{ "info": { "author": "Karolina Finc, Mateusz Chojnowski, Kamil Bona", "author_email": "karolinafinc@gmail.com, zygfrydwagner@gmail.com, kongokou@gmail.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 3 - Alpha", "Environment :: Console", "Intended Audience :: Science/Research", "License :: OSI Approved :: Apache Software License", "Programming Language :: Python :: 3" ], "description": "# fMRIDenoise - automated denoising, denoising strategies comparison, and functional connectivity data quality control.\n\n[](https://zenodo.org/record/3243178)\n[](https://travis-ci.org/nbraingroup/fmridenoise)\n \nTool for automatic denoising, denoising strategies comparisons,\nand functional connectivity data quality control.\nThe goal of fMRIDenoise is to provide an objective way to select\nbest-performing denoising strategy given the data.\nFMRIDenoise is designed to work directly on [fMRIPrep](https://fmriprep.readthedocs.io)-preprocessed datasets and\ndata in [BIDS](https://bids.neuroimaging.io/) standard.\nWe believe that the tool can make the selection of the denoising strategy more objective and also help researchers to obtain FC quality control metrics with almost no effort.\n\n**The project is in alpha stage and we are looking for feedback and collaborators.**\n\nProblem\n=======\n\n![Alt text](docs/fmridenoise_problem.png?raw=true \"Title\")\n\nSolution\n========\n\n![Alt text](docs/fmridenoise_solution.png?raw=true \"Title\")\n\nInstallation\n============\n\n**In a project directory run:**\n\n python setup.py install (--user)\n\n**To install fmridenoise from PyPi run:**\n \n pip install fmridenoise (--user)\n\nExecution\n=========\n\n**fmridenoise or python -m fmridenoise**\n\n usage: fmridenoise [-h] [-sub SUBJECTS [SUBJECTS ...]]\n [-ses SESSIONS [SESSIONS ...]] [-t TASKS [TASKS ...]]\n [-p PIPELINES [PIPELINES ...]]\n [-d DERIVATIVES [DERIVATIVES ...]] [--high-pass HIGH_PASS]\n [--low-pass LOW_PASS] [--MultiProc] [--profiler PROFILER]\n [-g] [--graph GRAPH] [--dry]\n bids_dir\n\n positional arguments:\n bids_dir Path do preprocessed BIDS dataset.\n\n optional arguments:\n -h, --help Show help message and exit.\n -sub SUBJECTS [SUBJECTS ...], --subjects SUBJECTS [SUBJECTS ...]\n List of subjects\n -ses SESSIONS [SESSIONS ...], --sessions SESSIONS [SESSIONS ...]\n List of session numbers, separated with spaces.\n -t TASKS [TASKS ...], --tasks TASKS [TASKS ...]\n List of tasks names, separated with spaces.\n -p PIPELINES [PIPELINES ...], --pipelines PIPELINES [PIPELINES ...]\n Name of pipelines used for denoising, can be both\n paths to json files with pipeline or name of pipelines\n from package.\n -d DERIVATIVES [DERIVATIVES ...], --derivatives DERIVATIVES [DERIVATIVES ...]\n Name (or list) of derivatives for which fmridenoise\n should be run. By default workflow looks for fmriprep\n dataset.\n --high-pass HIGH_PASS\n High pass filter value, deafult 0.008.\n --low-pass LOW_PASS Low pass filter value, default 0.08\n --MultiProc Run script on multiple processors, default False\n --profiler PROFILER Run profiler along workflow execution to estimate\n resources usage PROFILER is path to output log file.\n -g, --debug Run fmridenoise in debug mode - richer output, stops\n on first unchandled exception.\n --graph GRAPH Create workflow graph at GRAPH path\n --dry Perform everything except actually running workflow", "description_content_type": "text/markdown", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/nbraingroup/fmridenoise", "keywords": "", "license": "", "maintainer": "", "maintainer_email": "", "name": "fmridenoise", "package_url": "https://pypi.org/project/fmridenoise/", "platform": "", "project_url": "https://pypi.org/project/fmridenoise/", "project_urls": { "Homepage": "https://github.com/nbraingroup/fmridenoise" }, "release_url": "https://pypi.org/project/fmridenoise/0.1.5/", "requires_dist": null, "requires_python": "", "summary": "fMRIDenoise - 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