Detecting breast cancer from thermal infrared images by asymmetry analysis

Hairong Qi; Phani Teja Kuruganti; Wesley E. Snyder

Detecting breast cancer from thermal infrared images by asymmetry analysis

Hairong Qi, Phani Teja Kuruganti, Wesley E. Snyder

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

8 Scopus citations

Abstract

One of the popular methods for breast cancer detection is to make comparisons between contralateral images. When the images are relatively symmetrical, small asymmetries may indicate a suspicious region. In thermal infrared (IR) imaging, asymmetry analysis normally needs human intervention because of the difficulties in automatic segmentation. In order to provide a more objective diagnostic result, we describe an automatic approach to asymmetry analysis in thermograms. It includes automatic segmentation and supervised pattern classification. Experiments have been conducted based on images provided by Elliott Mastology Center (Inframetrics 600M camera) and Bioyear, Inc. (Microbolometer uncooled camera).

Original language	English
Title of host publication	Medical Devices and Systems
Publisher	CRC Press
Pages	27-1-27-14
ISBN (Electronic)	9781420003864
ISBN (Print)	0849321220, 9780849321221
State	Published - Jan 1 2006

Cite this

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abstract = "One of the popular methods for breast cancer detection is to make comparisons between contralateral images. When the images are relatively symmetrical, small asymmetries may indicate a suspicious region. In thermal infrared (IR) imaging, asymmetry analysis normally needs human intervention because of the difficulties in automatic segmentation. In order to provide a more objective diagnostic result, we describe an automatic approach to asymmetry analysis in thermograms. It includes automatic segmentation and supervised pattern classification. Experiments have been conducted based on images provided by Elliott Mastology Center (Inframetrics 600M camera) and Bioyear, Inc. (Microbolometer uncooled camera).",

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N2 - One of the popular methods for breast cancer detection is to make comparisons between contralateral images. When the images are relatively symmetrical, small asymmetries may indicate a suspicious region. In thermal infrared (IR) imaging, asymmetry analysis normally needs human intervention because of the difficulties in automatic segmentation. In order to provide a more objective diagnostic result, we describe an automatic approach to asymmetry analysis in thermograms. It includes automatic segmentation and supervised pattern classification. Experiments have been conducted based on images provided by Elliott Mastology Center (Inframetrics 600M camera) and Bioyear, Inc. (Microbolometer uncooled camera).

AB - One of the popular methods for breast cancer detection is to make comparisons between contralateral images. When the images are relatively symmetrical, small asymmetries may indicate a suspicious region. In thermal infrared (IR) imaging, asymmetry analysis normally needs human intervention because of the difficulties in automatic segmentation. In order to provide a more objective diagnostic result, we describe an automatic approach to asymmetry analysis in thermograms. It includes automatic segmentation and supervised pattern classification. Experiments have been conducted based on images provided by Elliott Mastology Center (Inframetrics 600M camera) and Bioyear, Inc. (Microbolometer uncooled camera).

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Detecting breast cancer from thermal infrared images by asymmetry analysis

Abstract

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