Paper
18 September 2001 Bronchoscopic fluorescence image enhancement using digital image processing techniques
Buhong Li, Shusen Xie, Zukang Lu
Author Affiliations +
Proceedings Volume 4549, Medical Image Acquisition and Processing; (2001) https://doi.org/10.1117/12.440273
Event: Multispectral Image Processing and Pattern Recognition, 2001, Wuhan, China
Abstract
Base on the analysis of the characteristics of bronchoscopic fluorescence image, four kinds of digital image processing (DIP) techniques are presented to enhance the contrast of fluorescence image between early lung cancer and surrounding normal tissues. Firstly, nearest neighbor averaging method is used to smooth noise that comes from different sources, which mainly including the photoelectric and electronic noise in the diagnostic system. Next, a method of enhancing contrast in fluorescence image is devised based on real-time digital subtraction of a background video image from a signal-plus-background video image. Then, segmental linearity image enhancement technique is applied after background subtraction to project the lesions. Finally, A processing technique for pseudocolor display of monochrome image is performed to enhance color contrast for the fluorescence image of early lung cancer, which highly enhanced the discrimination of lung cancer image in color. The validity of these approaches have been verified and primary clinical results show that a sufficient fluorescence contrast of suspicions versus normal tissue is obtained, which can effectively eliminate the false positive and negative diagnosis occurring in the clinical application.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Buhong Li, Shusen Xie, and Zukang Lu "Bronchoscopic fluorescence image enhancement using digital image processing techniques", Proc. SPIE 4549, Medical Image Acquisition and Processing, (18 September 2001); https://doi.org/10.1117/12.440273
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KEYWORDS
Luminescence

Image enhancement

Image filtering

Digital image processing

Tumors

Tissues

Image processing

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