Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/17028
Title: 3D neurological image retrieval with localized pathology-centric CMRGlc patterns
Authors: Cai, W
Liu, S
Wen, L
Eberl, S
Fulham, M
Feng, D
Keywords: keywords: {3D neurological image
Brain PET image
Dementia
Image retrieval
Localized retrieval
Issue Date: 2010
Publisher: IEEE
Source: 2010 17th IEEE International Conference on Image Processing (ICIP), 26-29 September 2010, Hong Kong, p. 3201-3204 How to cite?
Abstract: Functional neuroimaging has an important role in non-invasive diagnosis of neurodegenerative disorders. There are now large volumes of imaging data generated by functional imaging technologies and so there is a need to efficiently manage and retrieve these data. In this paper, we propose a new scheme for efficient 3D content-based neurological image retrieval. 3D pathology-centric masks were adaptively designed and applied for extracting CMRGlc (cerebral metabolic rate of glucose consumption) texture features with volumetric co-occurrence matrices from neurological FDG PET images. Our results, using 93 clinical dementia studies, show that our approach offers a robust and efficient retrieval mechanism for relevant clinical cases and provides advantages in image data analysis and management.
URI: http://hdl.handle.net/10397/17028
ISBN: 978-1-4244-7992-4
978-1-4244-7993-1 (E-ISBN)
ISSN: 1522-4880
DOI: 10.1109/ICIP.2010.5651869
Appears in Collections:Conference Paper

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