Thesis supervisor: Fernando Vilariño
Place:Â Computer Vision Centre at Lecture Room.
Committee:
Dr. Gloria Fernández. Hospital ClÃnic de Barcelona – Univ. de Barcelona. Spain.
Dr. Oriol Ramos. Departament de Ciències de la Computació – UAB, Centre de Visió per Computador. Barcelona. Spain.
Dr. Michał Drożdżal. R&D Department of Medtronic. Yoqneam. Israel.
Colorectal cancer is the third most common cancer worldwide and the second most common malignant tumor in Europe. Screening tests have shown to be very e ective in increasing the
survival rates since they allow an early detection of polyps. Among the di erent screening techniques, colonoscopy is considered the gold standard although clinical studies mention
several problems that have an impact in the quality of the procedure. The navigation through the rectum and colon track can be challenging for the physicians which can increase
polyp miss rates. The thorough visualization of the colon track must be ensured so that the chances of missing lesions are minimized. The visual analysis of colonoscopy images can
provide important information to the physicians and support their navigation during the procedure.
Blood vessels and their branching patterns can provide descriptive power to potentially develop biometric markers. Anatomical markers based on blood vessel patterns could be used
to identify a particular scene in colonoscopy videos and to support endoscope navigation by generating a sequence of ordered scenes through the di erent colon sections. By verifying the
presence of vascular content in the endoluminal scene it is also possible to certify a proper inspection of the colon mucosa and to improve polyp localization. Considering the potential
uses of blood vessel description, this contribution studies the characterization of the vascular content and the analysis of the descriptive power of its branching patterns.
Blood vessel characterization in colonoscopy images is shown to be a challenging task. The endoluminal scene is conformed by several elements whose similar characteristics hinder
the development of particular models for each of them. To overcome such diculties we propose the use of the blood vessel branching characteristics as key features for pattern
description. We present a model to characterize junctions in binary patterns. The implementation of the junction model allows us to develop a junction localization method. We
created two data sets including manually labeled vessel information as well as manual ground truths of two types of keypoint landmarks: junctions and endpoints. The proposed method
outperforms the available algorithms in the literature in experiments in both, our newly created colon vessel data set, and in DRIVE retinal fundus image data set. In the latter
case, we created a manual ground truth of junction coordinates. Since we want to explore the descriptive potential of junctions and vessels, we propose a graph-based approach to
create anatomical markers. In the context of polyp localization, we present a new method to inhibit the in uence of blood vessels in the extraction valley-pro le information. The results
show that our methodology decreases vessel in uence, increases polyp information and leads to an improvement in state-of-the-art polyp localization performance. We also propose a
polyp-speci c segmentation method that outperforms other general and speci c approaches.
