{"action":"created","comment":{"url":"https://api.github.com/repos/nilearn/nilearn/pulls/comments/46656692","id":46656692,"diff_hunk":"@@ -0,0 +1,186 @@\n+.. _region_extraction:\n+\n+===================================================================\n+Region Extraction for better brain parcellations\n+===================================================================\n+\n+.. topic:: **Page summary**\n+\n+   This section shows how to use Region Extractor to extract each connected\n+   brain regions/components into a separate brain activation regions and also\n+   shows how to learn functional connectivity interactions between each\n+   separate regions.\n+\n+.. contents:: **Contents**\n+    :local:\n+    :depth: 1\n+\n+\n+.. topic:: **References**\n+\n+   * `Abraham et al. \"Region segmentation for sparse decompositions: better\n+     brain parcellations from rest fMRI\", Sparsity Techniques in Medical Imaging,\n+     Sep 2014 <https://hal.inria.fr/hal-01093944>`_\n+\n+.. currentmodule:: nilearn.datasets\n+\n+Fetching resting state functional datasets\n+==========================================\n+\n+We use ADHD resting state functional connectivity datasets of 20 subjects,\n+which is already preprocessed and publicly available at\n+`<http://fcon_1000.projects.nitrc.org/indi/adhd200/>`_. We use utilities\n+:func:`fetch_adhd` implemented in nilearn for automatic fetching of these\n+datasets.\n+\n+\n+.. literalinclude:: ../../examples/connectivity/plot_extract_regions_canica_maps.py\n+    :start-after: # utilities\n+    :end-before: ################################################################################","path":"doc/connectivity/region_extraction.rst","position":39,"original_position":39,"commit_id":"b851452bfc933f78ee1c4e42188744a8c5f14c52","original_commit_id":"b851452bfc933f78ee1c4e42188744a8c5f14c52","user":{"login":"GaelVaroquaux","id":208217,"avatar_url":"https://avatars.githubusercontent.com/u/208217?v=3","gravatar_id":"","url":"https://api.github.com/users/GaelVaroquaux","html_url":"https://github.com/GaelVaroquaux","followers_url":"https://api.github.com/users/GaelVaroquaux/followers","following_url":"https://api.github.com/users/GaelVaroquaux/following{/other_user}","gists_url":"https://api.github.com/users/GaelVaroquaux/gists{/gist_id}","starred_url":"https://api.github.com/users/GaelVaroquaux/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/GaelVaroquaux/subscriptions","organizations_url":"https://api.github.com/users/GaelVaroquaux/orgs","repos_url":"https://api.github.com/users/GaelVaroquaux/repos","events_url":"https://api.github.com/users/GaelVaroquaux/events{/privacy}","received_events_url":"https://api.github.com/users/GaelVaroquaux/received_events","type":"User","site_admin":false},"body":"Based on the CircleCI rendering, it seems to be working as we would like:\r\nhttps://circle-artifacts.com/gh/nilearn/nilearn/870/artifacts/0/home/ubuntu/nilearn/doc/_build/html/connectivity/region_extraction.html\r\n\r\nSo I guess that it is OK.","created_at":"2015-12-04T07:51:53Z","updated_at":"2015-12-04T07:51:53Z","html_url":"https://github.com/nilearn/nilearn/pull/651#discussion_r46656692","pull_request_url":"https://api.github.com/repos/nilearn/nilearn/pulls/651","_links":{"self":{"href":"https://api.github.com/repos/nilearn/nilearn/pulls/comments/46656692"},"html":{"href":"https://github.com/nilearn/nilearn/pull/651#discussion_r46656692"},"pull_request":{"href":"https://api.github.com/repos/nilearn/nilearn/pulls/651"}}},"pull_request":{"url":"https://api.github.com/repos/nilearn/nilearn/pulls/651","id":39828251,"html_url":"https://github.com/nilearn/nilearn/pull/651","diff_url":"https://github.com/nilearn/nilearn/pull/651.diff","patch_url":"https://github.com/nilearn/nilearn/pull/651.patch","issue_url":"https://api.github.com/repos/nilearn/nilearn/issues/651","number":651,"state":"open","locked":false,"title":"[MRG] Region Extractor","user":{"login":"KamalakerDadi","id":11410385,"avatar_url":"https://avatars.githubusercontent.com/u/11410385?v=3","gravatar_id":"","url":"https://api.github.com/users/KamalakerDadi","html_url":"https://github.com/KamalakerDadi","followers_url":"https://api.github.com/users/KamalakerDadi/followers","following_url":"https://api.github.com/users/KamalakerDadi/following{/other_user}","gists_url":"https://api.github.com/users/KamalakerDadi/gists{/gist_id}","starred_url":"https://api.github.com/users/KamalakerDadi/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/KamalakerDadi/subscriptions","organizations_url":"https://api.github.com/users/KamalakerDadi/orgs","repos_url":"https://api.github.com/users/KamalakerDadi/repos","events_url":"https://api.github.com/users/KamalakerDadi/events{/privacy}","received_events_url":"https://api.github.com/users/KamalakerDadi/received_events","type":"User","site_admin":false},"body":"Fix #633 \r\nTo Do List:\r\n- [x] Code\r\n- [x] Documentation\r\n- [x] Tests\r\n- [x] Example\r\n\r\n* Code design\r\n   * ```class``` named as ```RegionExtractor``` - to *extract regions* from the maps and also extracts *subjects timeseries signals* from those extracted regions by inheriting ```NiftiMapsMasker```.\r\n         * function named as ```threshold_img``` to keep meaningful voxels for region extraction.\r\n         * function named as ```connected_regions``` to extract regions from thresholded images.\r\n\r\n*  ``` RegionExtractor ```\r\n      * ```fit()``` extract regions.\r\n      * ```transform()``` regions to signals.\r\n         * example: ```plot_extract_regions_canica_maps.py``` \r\n         * example: ```plot_extract_regions_smith_atlas_networks.py```\r\n\r\n*  ```threshold_img``` - two different ways of thresholding. (integrated in ```nilearn.image.image```)\r\n      1. ```percentile``` - ```scoreatpercentile```.\r\n      2. ```img_value``` - based on voxel intensity value.\r\n          * example: ```plot_extract_regions_statistical_maps.py```\r\n\r\n*  ```connected_regions``` - two different ways of extracting regions.\r\n      1. ```local_regions``` uses random walker method.\r\n      2. ```connected_components``` uses only labelling which labels based on unique features. \r\n           * example: ```plot_extract_regions_statistical_maps.py```\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n","created_at":"2015-07-13T16:08:17Z","updated_at":"2015-12-04T07:51:53Z","closed_at":null,"merged_at":null,"merge_commit_sha":"f8d036bd464aba6c511c0781d662677dd3285ad1","assignee":null,"milestone":null,"commits_url":"https://api.github.com/repos/nilearn/nilearn/pulls/651/commits","review_comments_url":"https://api.github.com/repos/nilearn/nilearn/pulls/651/comments","review_comment_url":"https://api.github.com/repos/nilearn/nilearn/pulls/comments{/number}","comments_url":"https://api.github.com/repos/nilearn/nilearn/issues/651/comments","statuses_url":"https://api.github.com/repos/nilearn/nilearn/statuses/b851452bfc933f78ee1c4e42188744a8c5f14c52","head":{"label":"KamalakerDadi:AutoExtractor","ref":"AutoExtractor","sha":"b851452bfc933f78ee1c4e42188744a8c5f14c52","user":{"login":"KamalakerDadi","id":11410385,"avatar_url":"https://avatars.githubusercontent.com/u/11410385?v=3","gravatar_id":"","url":"https://api.github.com/users/KamalakerDadi","html_url":"https://github.com/KamalakerDadi","followers_url":"https://api.github.com/users/KamalakerDadi/followers","following_url":"https://api.github.com/users/KamalakerDadi/following{/other_user}","gists_url":"https://api.github.com/users/KamalakerDadi/gists{/gist_id}","starred_url":"https://api.github.com/users/KamalakerDadi/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/KamalakerDadi/subscriptions","organizations_url":"https://api.github.com/users/KamalakerDadi/orgs","repos_url":"https://api.github.com/users/KamalakerDadi/repos","events_url":"https://api.github.com/users/KamalakerDadi/events{/privacy}","received_events_url":"https://api.github.com/users/KamalakerDadi/received_events","type":"User","site_admin":false},"repo":{"id":32379132,"name":"nilearn","full_name":"KamalakerDadi/nilearn","owner":{"login":"KamalakerDadi","id":11410385,"avatar_url":"https://avatars.githubusercontent.com/u/11410385?v=3","gravatar_id":"","url":"https://api.github.com/users/KamalakerDadi","html_url":"https://github.com/KamalakerDadi","followers_url":"https://api.github.com/users/KamalakerDadi/followers","following_url":"https://api.github.com/users/KamalakerDadi/following{/other_user}","gists_url":"https://api.github.com/users/KamalakerDadi/gists{/gist_id}","starred_url":"https://api.github.com/users/KamalakerDadi/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/KamalakerDadi/subscriptions","organizations_url":"https://api.github.com/users/KamalakerDadi/orgs","repos_url":"https://api.github.com/users/KamalakerDadi/repos","events_url":"https://api.github.com/users/KamalakerDadi/events{/privacy}","received_events_url":"https://api.github.com/users/KamalakerDadi/received_events","type":"User","site_admin":false},"private":false,"html_url":"https://github.com/KamalakerDadi/nilearn","description":"Machine 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