@inproceedings{14dc18a3212146ee90d1eea520e8f765,
title = "Pathology-centric medical image retrieval with hierarchical contextual spatial descriptor",
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 = "Retrieval, context, local, spatial, tumor",
author = "Yang Song and Weidong Cai and Yun Zhou and Lingfeng Wen and Feng, {David Dagan}",
year = "2013",
doi = "10.1109/ISBI.2013.6556446",
language = "English",
isbn = "9781467364546",
series = "Proceedings - International Symposium on Biomedical Imaging",
pages = "198--201",
booktitle = "ISBI 2013 - 2013 IEEE 10th International Symposium on Biomedical Imaging",
note = "2013 IEEE 10th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2013 ; Conference date: 07-04-2013 Through 11-04-2013",
}