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1.
J Biophotonics ; 11(1)2018 01.
Artigo em Inglês | MEDLINE | ID: mdl-28464418

RESUMO

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.


Assuntos
Esôfago , Fenômenos Ópticos , Análise Espectral/instrumentação , Animais , Anisotropia , Desenho de Equipamento , Suínos
2.
J Biophotonics ; 10(4): 553-564, 2017 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-27403639

RESUMO

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.


Assuntos
Endoscopia , Análise Espectral , Gravação em Vídeo , Adenocarcinoma/classificação , Adenocarcinoma/diagnóstico por imagem , Adenocarcinoma/tratamento farmacológico , Adenocarcinoma/patologia , Idoso , Idoso de 80 Anos ou mais , Endoscopia/instrumentação , Desenho de Equipamento , Feminino , Humanos , Modelos Lineares , Masculino , Pessoa de Meia-Idade , Curva ROC , Análise Espectral/instrumentação , Estômago/diagnóstico por imagem , Estômago/patologia , Neoplasias Gástricas/classificação , Neoplasias Gástricas/diagnóstico por imagem , Neoplasias Gástricas/tratamento farmacológico , Neoplasias Gástricas/patologia , Máquina de Vetores de Suporte , Gravação em Vídeo/instrumentação
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