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.
['Kazuhito Sato', 'Sakura Kadowaki', 'Hirokazu Madokoro', 'Atsushi Inugami']
Development of comparative reading system using 1D SOM for brain dock examinations