NDLI: Graph modeling and mining methods for brain images

Content Provider	Springer Nature Link
Author	Gao, Linlin Pan, Haiwei Xie, Xiaoqin Zhang, Zhiqiang Li, Qing Han, Qilong
Copyright Year	2016
Abstract	Brain disease is a top cause of death. Currently, its main diagonosis is to take advantage of medical brain images to analyse patients’ condition. In medical big data analysis field, it has been a research hotspot that how to effectively represent medical images and discover significant information hidden in them to further assist doctors to achieve a better diagnosis. Graphs, as one of the most general forms of data representation, can easily represent entities, their attributes and their relationships well. However, the existing medical image graph models do not exploit the specific relationships of brain images very well so that some essential information is lost. Therefore, aiming at brain images, we firstly construct a domain knowledge-oriented graph about the Topological Relationships among Ventricles and Lesions (TRVL) to represent a brain image, and give the algorithm of modeling a brain Image to a TRVL Graph (denoted as I2G). Then we propose a method named Frequent Approximate Subgraph Mining based on Graph Edit Distance (FASMGED) to exactly discover meaningful patterns hidden in brain images. This method employs a strong error-tolerant graph matching strategy which is accordant with ubiquitous noise in practice. Moreover, an approximate method of frequent approximate subgraph mining is proposed based on the greedy strategy. We have evaluated our algorithms on real and simulated data. Results show that I2G is computationally scalable, FASMGED can discover more significant patterns than other state-of-the-art frequent subgraph mining methods, and the approximate method of frequent approximate subgraph mining outperforms FASMGED.
Starting Page	9333
Ending Page	9369
Page Count	37
File Format	PDF
ISSN	13807501
Journal	Multimedia Tools and Applications
Volume Number	75
Issue Number	15
e-ISSN	15737721
Language	English
Publisher	Springer US
Publisher Date	2016-05-17
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Brain images Graph model Graph edit distance Frequent approximate subgraph mining Multimedia Information Systems Computer Communication Networks Data Structures, Cryptology and Information Theory Special Purpose and Application-Based Systems
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications Hardware and Architecture Software Media Technology

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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