NDLI: Dataset of Magnetic Resonance Images of Nonepileptic Subjects and Temporal Lobe Epilepsy Patients for Validation of Hippocampal Segmentation Techniques

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Neuroinformatics : Volume 9, Issue 2-3, September 2011

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Dataset of Magnetic Resonance Images of Nonepileptic Subjects and Temporal Lobe Epilepsy Patients for Validation of Hippocampal Segmentation Techniques

Content Provider	Springer Nature Link
Author	Jafari Khouzani, Kourosh Elisevich, Kost V. Patel, Suresh Soltanian Zadeh, Hamid
Copyright Year	2011
Abstract	The hippocampus has become the focus of research in several neurodegenerative disorders. Automatic segmentation of this structure from magnetic resonance (MR) imaging scans of the brain facilitates this work. Segmentation techniques must be evaluated using a dataset of MR images with accurate hippocampal outlines generated manually. Manual segmentation is not a trivial task. Lack of a unique segmentation protocol and poor image quality are only two factors that have confounded the consistency required for comparative study. We have developed a publicly available dataset of T1-weighted (T1W) MR images of epileptic and nonepileptic subjects along with their hippocampal outlines to provide a means of evaluation of segmentation techniques. This dataset contains 50 T1W MR images, 40 epileptic and ten nonepileptic. All images were manually segmented by a widely used protocol. Twenty five images were selected for training and were provided with hippocampal labels. Twenty five other images were provided without labels for testing algorithms. The users are allowed to evaluate their generated labels for the test images using 11 segmentation similarity metrics. Using this dataset, we evaluated two segmentation algorithms, Brain Parser and Classifier Fusion and Labeling (CFL), trained by the training set. For Brain Parser, an average Dice coefficient of 0.64 was obtained with the testing set. For CFL, this value was 0.75. Such findings indicate a need for further improvement of segmentation algorithms in order to enhance reliability.
Starting Page	335
Ending Page	346
Page Count	12
File Format	PDF
ISSN	15392791
Journal	Neuroinformatics
Volume Number	9
Issue Number	4
e-ISSN	15590089
Language	English
Publisher	Springer-Verlag
Publisher Date	2011-02-01
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Segmentation algorithm Hippocampus Magnetic resonance imaging Validation Computer Application in Life Sciences Bioinformatics Computational Biology/Bioinformatics Neurology Neurosciences
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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