NDLI: Information measures-based intensity standardization of MRI

Content Provider	IEEE Xplore Digital Library
Author	He, Renjie Sushmita Datta, Guozhi Tao, Narayana, Ponnada A.
Copyright Year	2008
Description	Author affiliation: Department of Diagnostic and Interventional Imaging, University of Texas Medical School at Houston, 77030, USA (He, Renjie; Sushmita Datta,; Guozhi Tao,; Narayana, Ponnada A.)
Abstract	Scan-to-scan intensity variation, even with the same imaging modality, affects a number of intensity-based image processing methods such as feature map based segmentation and non-rigid registration techniques that minimize sum of squared differences (SSD). Current intensity standardization techniques based on either percentile alignment or polynomial mapping suffer from a number of limitations. We present a novel intensity standardization techniques that exploits information measures obtained from the images. A probability similarity measure obtained by using polynomial mapping with Kullback-Leibler (KL) divergence is used for intensity standardization of pair-wise magnetic resonance (MR) images. For standardization of group-wise MR images, polynomial mapping with minimum entropy as a group probability similarity measure is used for attaining standardization in a group to attain common feature without bias. Our method is more flexible, particularly in mapping high intensity regions, such as lesions, since it does not set any hard limit. The mappings were realized through optimization of cost functions with Powell's search. The performance of the proposed method is demonstrated for non-rigid registration and feature map-based image segmentation of MR brain images.
Starting Page	2233
Ending Page	2236
File Size	605211
Page Count	4
File Format	PDF
ISBN	9781424418145
ISSN	1557170X
DOI	10.1109/IEMBS.2008.4649640
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-08-20
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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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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