Title :
Pathology-centric medical image retrieval with hierarchical contextual spatial descriptor
Author :
Yang Song ; Weidong Cai ; Yun Zhou ; Lingfeng Wen ; Feng, David Dagan
Author_Institution :
Biomed. & Multimedia Inf. Technol. (BMIT) Res. Group, Univ. of Sydney, Sydney, NSW, Australia
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.
Keywords :
cancer; cellular biophysics; computerised tomography; feature extraction; hierarchical systems; image representation; image retrieval; lung; medical image processing; positron emission tomography; NSCLC; PET-CT image; content-based image retrieval; hierarchical contextual spatial descriptor; medical diagnosis; nonsmall cell lung cancer; patch-based local feature extraction; pathological characteristics; pathology-centric feature extraction; pathology-centric feature representation; pathology-centric medical image retrieval; positron emission tomography-computed tomography image; standard feature descriptor; Biomedical imaging; Feature extraction; Image retrieval; Lungs; Pathology; Tumors; Vectors; Retrieval; context; local; spatial; tumor;
Conference_Titel :
Biomedical Imaging (ISBI), 2013 IEEE 10th International Symposium on
Conference_Location :
San Francisco, CA
Print_ISBN :
978-1-4673-6456-0
DOI :
10.1109/ISBI.2013.6556446