NDLI: Fast Automatic Segmentation of White Matter Streamlines Based on a Multi-Subject Bundle Atlas

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SpineCreator: a Graphical User Interface for the Creation of Layered Neural Models

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Automating NEURON Simulation Deployment in Cloud Resources

Fast Automatic Segmentation of White Matter Streamlines Based on a Multi-Subject Bundle Atlas

Collection of Simulated Data from a Thalamocortical Network Model

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Erratum to: Multi-Atlas Library for Eliminating Normalization Failures in Non-Human Primates

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Fast Automatic Segmentation of White Matter Streamlines Based on a Multi-Subject Bundle Atlas

Content Provider	Springer Nature Link
Author	Labra, Nicole Guevara, Pamela Duclap, Delphine Houeu, Josselin Poupon, Cyril Mangin, Jean François Figueroa, Miguel
Copyright Year	2016
Abstract	This paper presents an algorithm for fast segmentation of white matter bundles from massive dMRI tractography datasets using a multisubject atlas. We use a distance metric to compare streamlines in a subject dataset to labeled centroids in the atlas, and label them using a per-bundle configurable threshold. In order to reduce segmentation time, the algorithm first preprocesses the data using a simplified distance metric to rapidly discard candidate streamlines in multiple stages, while guaranteeing that no false negatives are produced. The smaller set of remaining streamlines is then segmented using the original metric, thus eliminating any false positives from the preprocessing stage. As a result, a single-thread implementation of the algorithm can segment a dataset of almost 9 million streamlines in less than 6 minutes. Moreover, parallel versions of our algorithm for multicore processors and graphics processing units further reduce the segmentation time to less than 22 seconds and to 5 seconds, respectively. This performance enables the use of the algorithm in truly interactive applications for visualization, analysis, and segmentation of large white matter tractography datasets.
Starting Page	71
Ending Page	86
Page Count	16
File Format	PDF
ISSN	15392791
Journal	Neuroinformatics
Volume Number	15
Issue Number	1
e-ISSN	15590089
Language	English
Publisher	Springer US
Publisher Date	2016-10-08
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Diffusion-weighted MRI HARDI data White matter tracts Tractography segmentation Streamline distance GPU programming Neurosciences Bioinformatics Computational Biology/Bioinformatics Computer Application in Life Sciences Neurology
Content Type	Text
Resource Type	Article
Subject	Neuroscience Information Systems Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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Fast Automatic Segmentation of White Matter Streamlines Based on a Multi-Subject Bundle Atlas

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