Hierarchical and binary spatial descriptors for lung nodule image retrieval

Gillian Ng; Yang Song; Weidong Cai; Yun Zhou; Sidong Liu; David Dagan Feng

doi:10.1109/EMBC.2014.6945108

Hierarchical and binary spatial descriptors for lung nodule image retrieval

Gillian Ng
, Yang Song
, Weidong Cai
, Yun Zhou
, Sidong Liu
, David Dagan Feng

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Scopus citations

Abstract

With the increasing amount of image data available for cancer staging and diagnosis, it is clear that content-based image retrieval techniques are becoming more important to assist physicians in making diagnoses and tracking disease. Domain-specific feature descriptors have been previously shown to be effective in the retrieval of lung tumors. This work proposes a method to improve the rotation invariance of the hierarchical spatial descriptor, as well as presents a new binary descriptor for the retrieval of lung nodule images. The descriptors were evaluated on the ELCAP public access database, exhibiting good performance overall.

Original language	English
Title of host publication	2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	6463-6466
Number of pages	4
ISBN (Electronic)	9781424479290
DOIs	https://doi.org/10.1109/EMBC.2014.6945108
State	Published - Nov 2 2014
Externally published	Yes
Event	2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 - Chicago, United States Duration: Aug 26 2014 → Aug 30 2014

Publication series

Name	2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014

Conference

Conference	2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
Country/Territory	United States
City	Chicago
Period	08/26/14 → 08/30/14

Access to Document

10.1109/EMBC.2014.6945108

Cite this

Ng, G., Song, Y., Cai, W., Zhou, Y., Liu, S., & Dagan Feng, D. (2014). Hierarchical and binary spatial descriptors for lung nodule image retrieval. In 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 (pp. 6463-6466). Article 6945108 (2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2014.6945108

Ng, Gillian ; Song, Yang ; Cai, Weidong et al. / Hierarchical and binary spatial descriptors for lung nodule image retrieval. 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 6463-6466 (2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014).

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title = "Hierarchical and binary spatial descriptors for lung nodule image retrieval",

abstract = "With the increasing amount of image data available for cancer staging and diagnosis, it is clear that content-based image retrieval techniques are becoming more important to assist physicians in making diagnoses and tracking disease. Domain-specific feature descriptors have been previously shown to be effective in the retrieval of lung tumors. This work proposes a method to improve the rotation invariance of the hierarchical spatial descriptor, as well as presents a new binary descriptor for the retrieval of lung nodule images. The descriptors were evaluated on the ELCAP public access database, exhibiting good performance overall.",

author = "Gillian Ng and Yang Song and Weidong Cai and Yun Zhou and Sidong Liu and \{Dagan Feng\}, David",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 ; Conference date: 26-08-2014 Through 30-08-2014",

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doi = "10.1109/EMBC.2014.6945108",

language = "English",

series = "2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014",

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Ng, G, Song, Y, Cai, W, Zhou, Y, Liu, S & Dagan Feng, D 2014, Hierarchical and binary spatial descriptors for lung nodule image retrieval. in 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014., 6945108, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014, Institute of Electrical and Electronics Engineers Inc., pp. 6463-6466, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014, Chicago, United States, 08/26/14. https://doi.org/10.1109/EMBC.2014.6945108

Hierarchical and binary spatial descriptors for lung nodule image retrieval. / Ng, Gillian; Song, Yang; Cai, Weidong et al.
2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 6463-6466 6945108 (2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Song, Yang

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AU - Zhou, Yun

AU - Liu, Sidong

AU - Dagan Feng, David

PY - 2014/11/2

Y1 - 2014/11/2

N2 - With the increasing amount of image data available for cancer staging and diagnosis, it is clear that content-based image retrieval techniques are becoming more important to assist physicians in making diagnoses and tracking disease. Domain-specific feature descriptors have been previously shown to be effective in the retrieval of lung tumors. This work proposes a method to improve the rotation invariance of the hierarchical spatial descriptor, as well as presents a new binary descriptor for the retrieval of lung nodule images. The descriptors were evaluated on the ELCAP public access database, exhibiting good performance overall.

AB - With the increasing amount of image data available for cancer staging and diagnosis, it is clear that content-based image retrieval techniques are becoming more important to assist physicians in making diagnoses and tracking disease. Domain-specific feature descriptors have been previously shown to be effective in the retrieval of lung tumors. This work proposes a method to improve the rotation invariance of the hierarchical spatial descriptor, as well as presents a new binary descriptor for the retrieval of lung nodule images. The descriptors were evaluated on the ELCAP public access database, exhibiting good performance overall.

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DO - 10.1109/EMBC.2014.6945108

M3 - Conference contribution

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AN - SCOPUS:84929485592

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BT - 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014

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Ng G, Song Y, Cai W, Zhou Y, Liu S, Dagan Feng D. Hierarchical and binary spatial descriptors for lung nodule image retrieval. In 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 6463-6466. 6945108. (2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014). doi: 10.1109/EMBC.2014.6945108

Hierarchical and binary spatial descriptors for lung nodule image retrieval

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