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In‐vivo multispectral video endoscopy towards in‐vivo hyperspectral video endoscopy
Author(s) -
Hohmann Martin,
Kanawade R.,
Klämpfl F.,
Douplik A.,
Mudter J.,
Neurath M. F.,
Albrecht H.
Publication year - 2017
Publication title -
journal of biophotonics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.877
H-Index - 66
eISSN - 1864-0648
pISSN - 1864-063X
DOI - 10.1002/jbio.201600021
Subject(s) - multispectral image , endoscopy , in vivo , hyperspectral imaging , medicine , computer vision , computer science , radiology , artificial intelligence , biology , microbiology and biotechnology
For in‐vivo diagnostics of cancer and pre‐cancer in the stomach, there is no endoscopic procedure offering both high sensitivity and high specificity. Our data suggest that multispectral or hyperspectral imaging may be helpful to solve this problem. It is successfully applied to the detection and analysis of easily reachable carcinomas, ex‐vivo samples of hollow organ mucosal carcinomas and also histological samples. An endoscopy system which allows flexible multispectral videoendoscopy for in‐vivo diagnostics has so far been unavailable. To overcome this problem, we modified a standard Olympus endoscopy system to conduct in‐vivo multispectral imaging of the upper GI tract. The pilot study is performed on 14 patients with adeno carcinomas in the stomach. For analysis, Support Vector Machine with linear and Gaussian Kernel, AdaBoost, RobustBoost and Random‐Forest‐walk are used and compared for the data classification with a leave‐one‐out strategy. The margin of the carcinoma for the training of the classifier is drawn by expert‐labeling. The cancer findings are cross‐checked by biopsies. We expect that the present study will help to improve the further development of hyperspectral endoscopy and to overcome some of the problems to be faced in this process.