Projektakademie Medizintechnik: LearnBarrida - Image Analysis and Machine Learning for Barrett Esophagus: Identification of Dysplasia and Adenocarcinoma

Barrett是一种食道粘膜组织的退行性变。它被认为是食管腺癌(EAC)的先兆。只有早期诊断为高度异型增生(HGD)或癌症的患者预后良好。EAC是癌症，在西方世界表现出最大的增长。不幸的是，在内窥镜操作过程中很难识别EAC或HGD。因此，在LearnBarrIDA项目中，医学图像计算和机器学习的方法将被适应和增强，以实现内窥镜彩色图像的自动分析并提取用于诊断的相关特征。一个成熟的计算机辅助诊断系统的可用性将有助于医生显著减少EAC/HGD的误诊数量，从而改善患者的预后。

Barrett is a degeneration of mucosal tissue in the esophagus. It is known as precursor of esophageal adenocarcinoma (EAC). Only diagnosed in an early stage of high grade dysplasia (HGD) or carcinoma patients have a good prognosis. EAC is the cancer, which shows the largest increase in the western world. Unfortunately, it is very difficult to identify EAC or HGD during an endoscopic procedure.Therefore, within the project LearnBarrIDA methods of medical image computing and machine learning will be adapted and enhanced to enable automatic analysis of endoscopic color images and extract relevant features for diagnosis. The availability of a mature computer assisted diagnosis system would help physicians to reduce the number of wrong diagnoses in cases of EAC/HGD significantly followed by a better prognosis for the patients.