DocumentCode :
3341243
Title :
Brain tissues segmentation for diagnosis of Alzheimer-type Dementia
Author :
Ito, Momoyo ; Sato, Kazuhito ; Fukumi, Minoru ; Namura, Ikuro
Author_Institution :
Inst. of Technol. & Sci., Univ. of Tokushima, Tokushima, Japan
fYear :
2011
fDate :
23-29 Oct. 2011
Firstpage :
3847
Lastpage :
3849
Abstract :
We proposed a segmentation method of brain tissues on T2-weighted MR frontal image. In our previous work, we showed an image diagnosis support system for Alzheimer-type Dementia that extracts temporal lobe regions and an intracranial region as regions of interest (ROI) from a T2-weighted MR frontal image and uses the cerebral atrophy rates at the ROI. In this paper, we specifically discuss segmentation of brain tissues which are used for calculation of atrophy rate. We proposed a brain tissue segmentation method using two kinds of unsupervised neural networks: Self-Organizing Maps (SOMs) and Fuzzy Adaptive Resonance Theory (ART). The performance of proposed method was tested in two brain MR images used in daily diagnosis. Proposed method could segment CSF accurately with continuity of brain tissues.
Keywords :
biological tissues; biomedical MRI; brain; diseases; feature extraction; fuzzy neural nets; image segmentation; medical image processing; self-organising feature maps; Alzheimer-type dementia; T2-weighted MR frontal image; brain tissue segmentation; cerebral atrophy rate; feature extraction; fuzzy adaptive resonance theory; image diagnosis support system; intracranial region; self-organizing maps; temporal lobe region; unsupervised neural network; Alzheimer´s disease; Image segmentation; Support vector machine classification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 2011 IEEE
Conference_Location :
Valencia
ISSN :
1082-3654
Print_ISBN :
978-1-4673-0118-3
Type :
conf
DOI :
10.1109/NSSMIC.2011.6153731
Filename :
6153731
Link To Document :
بازگشت