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Proceedings Paper

A new image calibration technique for colposcopic images
Author(s): Wenjing Li; Marcelo Soto-Thompson; Yizhi Xiong; Holger Lange
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Paper Abstract

Colposcopy is a primary diagnostic method used to detect cancer and precancerous lesions of the uterine cervix. During the examination, the metaplastic and abnormal tissues exhibit different degrees of whiteness (acetowhitening effect) after applying a 3%-5% acetic acid solution. Colposcopists evaluate the color and density of the acetowhite tissue to assess the severity of lesions for the purpose of diagnosis, telemedicine, and annotation. However, the color and illumination of the colposcopic images vary with the light sources, the instruments and camera settings, as well as the clinical environments. This makes assessment of the color information very challenging even for an expert. In terms of developing a Computer-Aided Diagnosis (CAD) system for colposcopy, these variations affect the performance of the feature extraction algorithm for the acetowhite color. Non-uniform illumination from the light source is also an obstacle for detecting acetowhite regions, lesion margins and anatomic features. Therefore, in digital colposcopy, it is critical to map the color appearance of the images taken with different colposcopes into one standard color space with normalized illumination. This paper presents a novel image calibration technique for colposcopic images. First, a specially designed calibration unit is mounted on the colposcope to acquire daily calibration data prior to performing patient examinations. The calibration routine is fast, automated, accurate and reliable. We then use our illumination correction algorithm and a color calibration algorithm to calibrate the patient data. In this paper we describe these techniques and demonstrate their applications in clinical studies.

Paper Details

Date Published: 20 March 2006
PDF: 12 pages
Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 614466 (20 March 2006); doi: 10.1117/12.650218
Show Author Affiliations
Wenjing Li, STI Medical Systems (United States)
Marcelo Soto-Thompson, STI Medical Systems (United States)
Yizhi Xiong, STI Medical Systems (United States)
Holger Lange, STI Medical Systems (United States)

Published in SPIE Proceedings Vol. 6144:
Medical Imaging 2006: Image Processing
Joseph M. Reinhardt; Josien P. W. Pluim, Editor(s)

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