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Author |
Joan M. Nuñez |
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Title |
Computer vision techniques for characterization of finger joints in X-ray image |
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Report |
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Year |
2011 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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165 |
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Keywords |
Rheumatoid arthritis, X-ray, Sharp Van der Heijde, joint characterization, sclerosis detection, bone detection, edge, ridge |
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Abstract |
Rheumatoid arthritis (RA) is an autoimmune inflammatory type of arthritis which mainly affects hands on its first stages. Though it is a chronic disease and there is no cure for it, treatments require an accurate assessment of illness evolution. Such assessment is based on evaluation of hand X-ray images by using one of the several available semi-quantitative methods. This task requires highly trained medical personnel. That is why the automation of the assessment would allow professionals to save time and effort. Two stages are involved in this task. Firstly, the joint detection, afterwards, the joint characterization. Unlike the little existing previous work, this contribution clearly separates those two stages and sets the foundations of a modular assessment system focusing on the characterization stage. A hand joint dataset is created and an accurate data analysis is achieved in order to identify relevant features. Since the sclerosis and the lower bone were decided to be the most important features, different computer vision techniques were used in order to develop a detector system for both of them. Joint space width measures are provided and their correlation with Sharp-Van der Heijde is verified |
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Address |
Bellaterra (Barcelona) |
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Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
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Editor |
Dr. Fernando Vilariño and Dra. Debora Gil |
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Notes  |
MV;IAM; |
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no |
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Call Number |
IAM @ iam @ Nuñ2011 |
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1795 |
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Author |
Joan M. Nuñez |
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Title |
Vascular Pattern Characterization in Colonoscopy Images |
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Book Whole |
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Year |
2015 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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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. |
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Address |
November 2015 |
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Corporate Author |
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Thesis |
Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
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Editor |
Fernando Vilariño |
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978-84-943427-6-9 |
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MV |
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no |
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Call Number |
Admin @ si @ Nuñ2015 |
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2709 |
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