3D NEUROLOGICAL IMAGE RETRIEVAL WITH LOCALIZED PATHOLOGY-CENTRIC CMRGLC PATTERNS

被引：26

作者：

Cai, Weidong ^{[1
]}

Liu, Sidong ^{[1
]}

Wen, Lingfeng ^{[1
]}

Eberl, Stefan ^{[1
]}

Fulham, Michael J. ^{[1
]}

Feng, Dagan ^{[1
]}

机构：

[1] Univ Sydney, Sch Informat Technol, Biomed & Multimedia Informat Technol BMIT Res Grp, Sydney, NSW 2006, Australia

来源：

2010 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING | 2010年

关键词：

3D neurological image; image retrieval; brain PET image; dementia; localized retrieval; SYSTEM;

D O I：

10.1109/ICIP.2010.5651869

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页码：3201 / 3204

页数：4

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