Towards More Reliability and Less Invasiveness in Celiac Disease Diagnosis: Computer-aided Detection and Assessment of Affected Mucosa in Endoscopic Video
Celiac disease (CD) is a common autoimmune disorder triggered by dietary gluten primarily affecting the small bowel. Endoscopy combined with intestinal biopsies is currently considered the gold standard for the diagnosis of CD. However, the histological staging is subject to significant intra- and inter-observer variability. This variability gives strong incentive to seek for supportive or alternative diagnostic methods. Therefore, a variety of new endoscopic techniques as well as a software for the analysis of endoscopic still images have been developed. If a software can detect villous atrophy not only in endoscopic still images but in video clips as well, in such cases, a small bowel biopsy could entirely be avoided. A biopsy-avoiding diagnostic approach saves costs, time, and manpower and simultaneously increases the safety of the procedure.
The main question we will try to assess is if such a software can be developed and easily integrated into the routine of pediatric endoscopy. Furthermore, we will examine if the narrow band imaging technique, an optical/digital chromoendoscopy, can further improve the reliability of automated analysis. Various feature extraction and classification strategies will be applied for automated differentiation between presence and absence of villous atrophy in the endoscopic video clips.
Methods and Skills:
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