Method of retrieving multi-scale objects from optical colonoscopy images based on image-recognition techniques

This paper proposes a method of retrieving multi-scale objects from optical colonoscopy images based on image-recognition techniques. Optical colonoscopy is the most common approach to diagnosing bowel diseases through direct colon and rectum inspections. Periodic optical-colonoscopy examinations are particularly important for detecting cancers at early stages while still treatable. However, diagnostic accuracy is highly dependent on both the experience and knowledge of the medical doctor. Moreover, it is extremely difficult, even for specialist doctors, to detect the early stages of cancer when obscured by inflammations of the colonic mucosa due to intractable inflammatory bowel diseases. In order to assist diagnoses with optical colonoscopy, this paper proposes a retrieval method for colonoscopy images that can cope with multi-scale objects. The proposed method can retrieve similar images despite varying sizes of the target objects. Through experiments conducted with real clinical colonoscopy images, we demonstrate that the method is able to retrieve objects of any size at high levels of accuracy.