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

• Applicant: Professor Dr. Christoph Palm
• Subject Area: Medical Physics, Biomedical Technology
• Term: from 2016 to 2018
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 332376560

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.

• DFG Programme: Research Grants