DocumentCode :
2486416
Title :
Development of comparative reading system using 1D SOM for brain dock examinations
Author :
Sato, Kazuhito ; Kadowaki, Sakura ; Madokoro, Hirokazu ; Inugami, Atsushi
Author_Institution :
Fac. of Syst. Sci. & Technol., Akita Prefectural Univ., Yurihonjo, Japan
fYear :
2010
fDate :
18-23 July 2010
Firstpage :
1
Lastpage :
7
Abstract :
We propose an objective segmentation method for Magnetic Resonance (MR) images of the brain using self-mapping characteristics of one-dimensional Self-Organizing Maps (SOM). The proposed method requires no operators to specify the representative points, but can segment tissues (such as cerebrospinal fluid, gray matter and white matter) needed for diagnosis of brain atrophy. Doing clinical image experiments, we demonstrate the effectiveness of our method. As a result, we can obtain segmentation results that agree with anatomical structures such as continuities and boundaries of brain tissues. In addition, we propose a Computer-Aided Diagnosis (CAD) system for brain dock examinations based on the use case analysis of diagnostic reading, and construct a prototype system for reducing loads to diagnosticians that occur in quantitative analyses of the extent of brain atrophy. Through field tests of 193 examples of brain dock medical examinees at Akita Kumiai General Hospital, we also present the prospect of efficient support of diagnostic reading in the clinical field because the aging situation of brain atrophy is readily quantifiable irrespective of diagnosticians´ expertise.
Keywords :
CAD; biological tissues; biomedical MRI; brain; image segmentation; medical image processing; self-organising feature maps; 1D SOM; Akita Kumiai General Hospital; brain atrophy; brain dock examinations; cerebrospinal fluid; clinical image experiments; comparative reading system; computer-aided diagnosis; diagnostic reading; magnetic resonance images; one-dimensional self-organizing maps; self-mapping characteristics; Diseases; Image segmentation; Magnetic resonance imaging;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks (IJCNN), The 2010 International Joint Conference on
Conference_Location :
Barcelona
ISSN :
1098-7576
Print_ISBN :
978-1-4244-6916-1
Type :
conf
DOI :
10.1109/IJCNN.2010.5596292
Filename :
5596292
Link To Document :
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