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1.
J Biophotonics ; 11(1)2018 01.
Article in English | MEDLINE | ID: mdl-28464418

ABSTRACT

Optical properties (µa , µs and g) of certain human tissue types such as skin and blood have been very well investigated. However until today, for internal body organs such as the esophagus they are not well characterized. For ex-vivo measurements "Inverse Adding Doubling" (IAD) and Inverse Monte-Carlo-Simulation (IMCS) are state of the art. Both methods need the measurement of the collimated transmission. Current methods lack a proper way of measuring the collimated transmission. Hence, this measurement of the g-factor has a systematic error. Therefore, for the measurement of the collimated transmission, a new approach has been developed and evaluated with intralipid. Finally, the optical properties of mucosa, sub mucosa, muscularis and adventitia of pig esophagus tissue are calculated with IAD. The results are promising and in agreement with published literature.


Subject(s)
Esophagus , Optical Phenomena , Spectrum Analysis/instrumentation , Animals , Anisotropy , Equipment Design , Swine
2.
J Biophotonics ; 10(4): 553-564, 2017 Apr.
Article in English | MEDLINE | ID: mdl-27403639

ABSTRACT

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.


Subject(s)
Endoscopy , Spectrum Analysis , Video Recording , Adenocarcinoma/classification , Adenocarcinoma/diagnostic imaging , Adenocarcinoma/drug therapy , Adenocarcinoma/pathology , Aged , Aged, 80 and over , Endoscopy/instrumentation , Equipment Design , Female , Humans , Linear Models , Male , Middle Aged , ROC Curve , Spectrum Analysis/instrumentation , Stomach/diagnostic imaging , Stomach/pathology , Stomach Neoplasms/classification , Stomach Neoplasms/diagnostic imaging , Stomach Neoplasms/drug therapy , Stomach Neoplasms/pathology , Support Vector Machine , Video Recording/instrumentation
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