Diagnosis of esophageal cancer via correlation coefficient of optical density
Journal
IMETI 2011 - 4th International Multi-Conference on Engineering and Technological Innovation, Proceedings
Journal Volume
2
Pages
142-145
ISBN
9.78194E+12
Date Issued
2011
Author(s)
Abstract
The currently used techniques for the detection of esophageal cancer usually rely on pathological examination after sectioning and ultrasound imaging. Optical methods have the advantages of better spatial resolution and sensitivity with minimal invasion. Therefore, the development of optical techniques will be helpful for the diagnosis of esophageal cancer at the early stage. In this research, we propose and develop an optical system for the detection of optical densities of biological samples in the visible range. Both the optical densities of normal and cancerous esophageal tissues from three independent patients as well as that of cultured esophageal cells were measured. After normalization of the spectra and calculation of the correlation coefficient of each pair of spectra with developed algorithms, the distribution of correlation coefficients was mapped for the identification of normal and cancerous tissues. We have also developed an algorithm which can quantitatively evaluate the possibility of a site of tissue to be cancerous. The results show significant distinguishability between normal and cancerous tissues and consistency with pathological examinations. Since the utilized light is in the visible range that is easy to be delivered in optical fibers, this technique is suitable for in vivo detection in the integration with endoscopes.
Subjects
Con-elation coefficient; Esophageal cancer; Optical density; Optical diagnosis; Spectrum analysis
SDGs
Other Subjects
Con-elation coefficient; Correlation coefficient; Distinguishability; Esophageal cancer; Esophageal tissues; Optical Diagnosis; Spatial resolution; Ultrasound imaging; Algorithms; Density (optical); Density measurement (optical); Diseases; Histology; Optical fibers; Optical systems; Spectrum analysis; Ultrasonic imaging; Tissue
Type
conference paper