DocumentCode
2617586
Title
Ventricles segmentation and matching for content - based medical image retrieval
Author
Tong, Hau-Lee ; Fauzi, Mohammad Faizal Ahmad ; Haw, Su-Cheng
Author_Institution
Fac. of Inf. Technol., Multimedia Univ., Cyberjaya, Malaysia
fYear
2010
fDate
10-13 May 2010
Firstpage
733
Lastpage
736
Abstract
In this paper, we propose a new methodology for the segmentation and retrieval system for Computed Tomography (CT) brain images. For the segmentation part, two segmentation techniques are considered which are modified FCM with population-diameter independent (PDI) and expectation-maximization (EM) segmentation. However, only one of the techniques is selected based on the average intensity in order to obtain the more proper results. The ultimate goal of the segmentation is to acquire the ventricles. For the retrieval part, features are extracted from the ventricles and images are retrieved based on the similarities of the ventricles. From the obtained experimental results, the proposed methodology is feasible and attains satisfactory results.
Keywords
brain; computerised tomography; content-based retrieval; expectation-maximisation algorithm; feature extraction; image matching; image retrieval; image segmentation; medical image processing; FCM; computed tomography brain images; content-based medical image retrieval; expectation-maximization segmentation; feature extraction; population-diameter independent; ventricles matching; ventricles segmentation; Barium; Brain; Feature extraction; Image segmentation; Medical diagnostic imaging; Weight measurement; Image segmentation; Medical image retrieval; Medical imaging;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Sciences Signal Processing and their Applications (ISSPA), 2010 10th International Conference on
Conference_Location
Kuala Lumpur
Print_ISBN
978-1-4244-7165-2
Type
conf
DOI
10.1109/ISSPA.2010.5605414
Filename
5605414
Link To Document