Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/25910
Title: Thoracic image case retrieval with spatial and contextual information
Authors: Song, Y
Cai, W
Eberl, S
Fulham, M
Feng, D
Keywords: PET-CT
Detection
Lymph nodes
Retrieval
Tumor
Issue Date: 2011
Publisher: IEEE
Source: 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, March 30 2011-April 2 2011, Chicago, IL, p. 1885-1888 How to cite?
Abstract: Positron emission tomography - computed tomography (PETCT) is now accepted as the best imaging technique to accurately stage lung cancer. The consistent and accurate interpretation of PET-CT images, however, is not a trivial task. We propose a content-based image retrieval system for retrieving similar cases from an imaging database as a reference dataset to aid the physicians in PET-CT scan interpretation. Problematic areas in diagnosis are the abnormal FDG uptake in the parenchymal lung tumor and in the regional nodes in the pulmonary hilar regions and the mediastinum. The primary tumor and the nodal disease are detected from the scans of thorax with learning-based techniques and a voting method for 3D object localization. Similar cases are then retrieved based on the similarity measure between the feature vectors of the cases. Our preliminary evaluation with clinical data from lung cancer patients suggests our approach is accurate with high retrieval precision.
URI: http://hdl.handle.net/10397/25910
ISBN: 978-1-4244-4127-3
978-1-4244-4128-0 (E-ISBN)
ISSN: 1945-7928
DOI: 10.1109/ISBI.2011.5872776
Appears in Collections:Conference Paper

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