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 proceedingConference proceeding contribution

5 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 languageEnglish
Title of host publication2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages6463-6466
Number of pages4
ISBN (Electronic)9781424479290
DOIs
Publication statusPublished - 2 Nov 2014
Externally publishedYes
Event2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 - Chicago, United States
Duration: 26 Aug 201430 Aug 2014

Conference

Conference2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
CountryUnited States
CityChicago
Period26/08/1430/08/14

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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). [6945108] Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/EMBC.2014.6945108