Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/28182
Title: Pathology-centric medical image retrieval with hierarchical contextual spatial descriptor
Authors: Song, Y
Cai, WD
Zhou, Y
Wen, LF
Feng, DD
Keywords: Retrieval
Context
Local
Spatial
Tumor
Issue Date: 2013
Publisher: IEEE
Source: 2013 IEEE 10th International Symposium on Biomedical Imaging (ISBI), 7-11 April 2013, San Francisco, CA, p. 198-201 How to cite?
Abstract: Content-based image retrieval has been suggested as an aid to medical diagnosis. Techniques based on standard feature descriptors, however, might not represent optimally the pathological characteristics in medical images. In this paper, we propose a new approach for medical image retrieval based on pathology-centric feature extraction and representation; and patch-based local feature extraction and hierarchical contextual spatial descriptor are designed. The proposed method is evaluated on positron emission tomography - computed tomography (PET-CT) images from subjects with non-small cell lung cancer (NSCLC), showing promising performance improvements over the other benchmarked techniques.
URI: http://hdl.handle.net/10397/28182
ISBN: 978-1-4673-6456-0
ISSN: 1945-7928
DOI: 10.1109/ISBI.2013.6556446
Appears in Collections:Conference Paper

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