Novel Method for Detection of Gastric Cancer by Hyperspectral Image Technique.

During the last few decades, many studies have been performed on the early detection of cancer.Gastric cancer causes about 8,00,00 deaths worldwide per year. The objective of the work is to develop a novel hyperspectral imaging algorithm for gastric cancer detection by the medical community, however, due to the amounts of data and the highly computational nature of the algorithms, running these complex algorithms can result computationally intensive. This paper, for the early detection of gastric cancer, proposes the analysis system of an endoscopic image of the stomach, which detects the abnormal region by using the change of color in the image and by providing the surface tissue information to the detector. While advanced inflammation and cancer may be easily detected, early inflammation and cancer are difficult to detect and requires more attention to be detected. This research proposes the implementation of the data bank that will provide the medical community with the necessary tools to develop novel algorithms for the early and accurate gastric cancer patents. Graphical processing unit provides the necessary computing power for the acceleration of the proposed algorithms in the data bank to their capability of running data parallel algorithms. The sensitivity, specificity and accuracy rates of the algorithm’s diagnostic capability will be enhanced by image processing.