NDLI: A neural network approach to unsupervised segmentation of single-channel MR images

Content Provider	IEEE Xplore Digital Library
Author	Morra, L. Lamberti, F. Demartini, C.
Copyright Year	2003
Description	Author affiliation: Dipt. di Automatica e Informatica, Politecnico di Torino, Italy (Morra, L.; Lamberti, F.; Demartini, C.)
Abstract	A novel neural network-based technique for segmentation of single-channel magnetic resonance images is presented. The segmentation of single-channel magnetic resonance images is a daunting task due to the relatively little information available at each pixel site. The proposed algorithm is based on unsupervised clustering by means of a Kohonen Self-Organizing Map: unsupervised segmentation algorithms are highly desirable in order to eliminate intra- and interobserver variability. Particular attention has been devoted to the choice of suitable features, in order to ensure an accurate and reliable segmentation: in particular, a feature set extracted from the neighborhood of each pixel has been evaluated. The proposed technique has been tested on simulated magnetic resonance images to assess its stability against the presence of noise and intensity inhomogeneities. Moreover, it has been tested on real magnetic resonance images of both volunteers and brain tumor patients. The preliminary results presented make the proposed technique a promising alternative for the segmentation of single-channel magnetic resonance images and encourage further investigation.
Starting Page	515
Ending Page	518
File Size	507621
Page Count	4
File Format	PDF
ISBN	0780375793
DOI	10.1109/CNE.2003.1196876
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-03-20
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Stability Neural networks Magnetic resonance Clustering algorithms Magnetic noise Feature extraction Brain modeling Pixel Testing
Content Type	Text
Resource Type	Article

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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
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