A Novel Statistical Approach for Brain MR Images Segmentation Based on Relaxation Times
Joint Authors
Pascazio, Vito
Baselice, Fabio
Ferraioli, Giampaolo
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-12-21
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Brain tissue segmentation in Magnetic Resonance Imaging is useful for a wide range of applications.
Classical approaches exploit the gray levels image and implement criteria for differentiating regions.
Within this paper a novel approach for brain tissue joint segmentation and classification is presented.
Starting from the estimation of proton density and relaxation times, we propose a novel method for identifying the optimal decision regions.
The approach exploits the statistical distribution of the involved signals in the complex domain.
The technique, compared to classical threshold based ones, is able to globally improve the classification rate.
The effectiveness of the approach is evaluated on both simulated and real datasets.
American Psychological Association (APA)
Baselice, Fabio& Ferraioli, Giampaolo& Pascazio, Vito. 2015. A Novel Statistical Approach for Brain MR Images Segmentation Based on Relaxation Times. BioMed Research International،Vol. 2015, no. 2015, pp.1-13.
https://search.emarefa.net/detail/BIM-1054399
Modern Language Association (MLA)
Baselice, Fabio…[et al.]. A Novel Statistical Approach for Brain MR Images Segmentation Based on Relaxation Times. BioMed Research International No. 2015 (2015), pp.1-13.
https://search.emarefa.net/detail/BIM-1054399
American Medical Association (AMA)
Baselice, Fabio& Ferraioli, Giampaolo& Pascazio, Vito. A Novel Statistical Approach for Brain MR Images Segmentation Based on Relaxation Times. BioMed Research International. 2015. Vol. 2015, no. 2015, pp.1-13.
https://search.emarefa.net/detail/BIM-1054399
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1054399