Automation of ROI extraction in hyperspectral breast images

B. Kim, N. Kehtarnavaz, P. Leboulluec, H. Liu, Y. Peng, David M Euhus

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The extraction of regions-of-interest (ROIs) in hyperspectral images of breast cancer specimens is currently carried out manually or by visual inspection. In order to address the labor-intensive and time-consuming process of the manual extraction of ROIs in hyperspectral images, an algorithm is developed in this paper to automate the extraction process. This is achieved by using a contrast module and a homogeneity module to duplicate the same manual or visual steps that an expert goes through in order to extract ROIs. The success of the automated process is determined by comparing the classification rates of the automated approach with the manual approach in terms of the ability to separate cancer cases from normal cases.

Original languageEnglish (US)
Title of host publicationProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Pages3658-3661
Number of pages4
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013 - Osaka, Japan
Duration: Jul 3 2013Jul 7 2013

Other

Other2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013
CountryJapan
CityOsaka
Period7/3/137/7/13

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ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

Cite this

Kim, B., Kehtarnavaz, N., Leboulluec, P., Liu, H., Peng, Y., & Euhus, D. M. (2013). Automation of ROI extraction in hyperspectral breast images. In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (pp. 3658-3661). [6610336] https://doi.org/10.1109/EMBC.2013.6610336