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 contribution

5 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 languageEnglish (US)
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 Inc.
Pages6463-6466
Number of pages4
ISBN (Print)9781424479290
DOIs
StatePublished - Nov 2 2014
Event2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 - Chicago, United States
Duration: Aug 26 2014Aug 30 2014

Other

Other2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
Country/TerritoryUnited States
CityChicago
Period8/26/148/30/14

ASJC Scopus subject areas

  • Health Informatics
  • Computer Science Applications
  • Biomedical Engineering

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