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 proceeding contribution › peer-review

6 Citations (Scopus)

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 (IEEE)
Pages	6463-6466
Number of pages	4
ISBN (Electronic)	9781424479290
DOIs	https://doi.org/10.1109/EMBC.2014.6945108
Publication status	Published - 2 Nov 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: 26 Aug 2014 → 30 Aug 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	26/08/14 → 30/08/14

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10.1109/EMBC.2014.6945108

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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 (pp. 6463-6466). Article 6945108 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/EMBC.2014.6945108

@inproceedings{8d80561061f946d88371eda0b394bf95,

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",

year = "2014",

month = nov,

day = "2",

doi = "10.1109/EMBC.2014.6945108",

language = "English",

pages = "6463--6466",

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

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

note = "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",

}

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, Institute of Electrical and Electronics Engineers (IEEE), pp. 6463-6466, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014, Chicago, United States, 26/08/14. 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 (IEEE), 2014. p. 6463-6466 6945108.

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

TY - GEN

T1 - Hierarchical and binary spatial descriptors for lung nodule image retrieval

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AU - Song, Yang

AU - Cai, Weidong

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.

UR - https://www.scopus.com/pages/publications/84929485592

U2 - 10.1109/EMBC.2014.6945108

DO - 10.1109/EMBC.2014.6945108

M3 - Conference proceeding contribution

C2 - 25571476

AN - SCOPUS:84929485592

SP - 6463

EP - 6466

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

PB - Institute of Electrical and Electronics Engineers (IEEE)

T2 - 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014

Y2 - 26 August 2014 through 30 August 2014

ER -

Hierarchical and binary spatial descriptors for lung nodule image retrieval

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