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Hyper spectral imaging is a possible way for disease detection. However, for carcinoma detection most of the results are  ex-vivo . However,  in-vivo  results of endoscopic studies still show fairly low accuracies in contrast to the good results of many  ex-vivo  studies. To overcome this problem and to provide a reasonable explanation, Monte-Carlo simulations of photon trajectories are proposed as a tool to generate multi spectral images including inter patient variations to simulate 40 patients. Furthermore, these simulations have the huge advantage that the position of the carcinoma is known. Due to this, the effect of mislabelled data can be studied. As shown in this study, a percentage of 30–35% of mislabelled data might lead to significant decrease of the accuracy from around 90% to around 70–75%. Therefore, the main focus of hyper spectral imaging has to be the exact characterization of the training data in the future.

Factors influencing the accuracy for tissue classification in multi spectral in-vivo endoscopy for the upper gastro-internal tract