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Jorge Bernal, F. Javier Sanchez, & Fernando Vilariño. (2011). "Integration of Valley Orientation Distribution for Polyp Region Identification in Colonoscopy " In In MICCAI 2011 Workshop on Computational and Clinical Applications in Abdominal Imaging (Vol. 6668, pp. 76–83). Lecture Notes in Computer Science. Springer Link.
Abstract: This work presents a region descriptor based on the integration of the information that the depth of valleys image provides. The depth of valleys image is based on the presence of intensity valleys around polyps due to the image acquisition. Our proposed method consists of defining, for each point, a series of radial sectors around it and then accumulates the maxima of the depth of valleys image only if the orientation of the intensity valley coincides with the orientation of the sector above. We apply our descriptor to a prior segmentation of the images and we present promising results on polyp detection, outperforming other approaches that also integrate depth of valleys information.
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Jorge Bernal, F. Javier Sanchez, & Fernando Vilariño. (2011). "Depth of Valleys Accumulation Algorithm for Object Detection " In 14th Congrès Català en Intel·ligencia Artificial (Vol. 1, pp. 71–80).
Abstract: This work aims at detecting in which regions the objects in the image are by using information about the intensity of valleys, which appear to surround ob- jects in images where the source of light is in the line of direction than the camera. We present our depth of valleys accumulation method, which consists of two stages: first, the definition of the depth of valleys image which combines the output of a ridges and valleys detector with the morphological gradient to measure how deep is a point inside a valley and second, an algorithm that denotes points of the image as interior to objects those which are inside complete or incomplete boundaries in the depth of valleys image. To evaluate the performance of our method we have tested it on several application domains. Our results on object region identification are promising, specially in the field of polyp detection in colonoscopy videos, and we also show its applicability in different areas.
Keywords: Object Recognition, Object Region Identification, Image Analysis, Image Processing
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Farhan Riaz, Fernando Vilariño, Mario Dinis-Ribeiro, & Miguel Coimbraln. (2011). "Identifying Potentially Cancerous Tissues in Chromoendoscopy Images " In and M. Hernandez J. M. S. J. Vitria (Ed.), 5th Iberian Conference on Pattern Recognition and Image Analysis (Vol. 6669, pp. 709–716). Berlin: Springer.
Abstract: The dynamics of image acquisition conditions for gastroenterology imaging scenarios pose novel challenges for automatic computer assisted decision systems. Such systems should have the ability to mimic the tissue characterization of the physicians. In this paper, our objective is to compare some feature extraction methods to classify a Chromoendoscopy image into two different classes: Normal and Potentially cancerous. Results show that LoG filters generally give best classification accuracy among the other feature extraction methods considered.
Keywords: Endoscopy, Computer Assisted Diagnosis, Gradient.
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Jorge Bernal, F. Javier Sanchez, & Fernando Vilariño. (2013). "Impact of Image Preprocessing Methods on Polyp Localization in Colonoscopy Frames " In 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (pp. 7350–7354).
Abstract: In this paper we present our image preprocessing methods as a key part of our automatic polyp localization scheme. These methods are used to assess the impact of different endoluminal scene elements when characterizing polyps. More precisely we tackle the influence of specular highlights, blood vessels and black mask surrounding the scene. Experimental results prove that the appropriate handling of these elements leads to a great improvement in polyp localization results.
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Jorge Bernal, F. Javier Sanchez, & Fernando Vilariño. (2012). "Towards Automatic Polyp Detection with a Polyp Appearance Model " . Pattern Recognition, 45(9), 3166–3182.
Abstract: This work aims at the automatic polyp detection by using a model of polyp appearance in the context of the analysis of colonoscopy videos. Our method consists of three stages: region segmentation, region description and region classification. The performance of our region segmentation method guarantees that if a polyp is present in the image, it will be exclusively and totally contained in a single region. The output of the algorithm also defines which regions can be considered as non-informative. We define as our region descriptor the novel Sector Accumulation-Depth of Valleys Accumulation (SA-DOVA), which provides a necessary but not sufficient condition for the polyp presence. Finally, we classify our segmented regions according to the maximal values of the SA-DOVA descriptor. Our preliminary classification results are promising, especially when classifying those parts of the image that do not contain a polyp inside.
Keywords: Colonoscopy,PolypDetection,RegionSegmentation,SA-DOVA descriptot
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Santiago Segui, Michal Drozdzal, Fernando Vilariño, Carolina Malagelada, Fernando Azpiroz, Petia Radeva, et al. (2012). "Categorization and Segmentation of Intestinal Content Frames for Wireless Capsule Endoscopy " . IEEE Transactions on Information Technology in Biomedicine, 16(6), 1341–1352.
Abstract: Wireless capsule endoscopy (WCE) is a device that allows the direct visualization of gastrointestinal tract with minimal discomfort for the patient, but at the price of a large amount of time for screening. In order to reduce this time, several works have proposed to automatically remove all the frames showing intestinal content. These methods label frames as {intestinal content – clear} without discriminating between types of content (with different physiological meaning) or the portion of image covered. In addition, since the presence of intestinal content has been identified as an indicator of intestinal motility, its accurate quantification can show a potential clinical relevance. In this paper, we present a method for the robust detection and segmentation of intestinal content in WCE images, together with its further discrimination between turbid liquid and bubbles. Our proposal is based on a twofold system. First, frames presenting intestinal content are detected by a support vector machine classifier using color and textural information. Second, intestinal content frames are segmented into {turbid, bubbles, and clear} regions. We show a detailed validation using a large dataset. Our system outperforms previous methods and, for the first time, discriminates between turbid from bubbles media.
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Joan M. Nuñez, Debora Gil, & Fernando Vilariño. (2013). "Finger joint characterization from X-ray images for rheymatoid arthritis assessment " In 6th International Conference on Biomedical Electronics and Devices (pp. 288–292). SciTePress.
Abstract: In this study we propose amodular systemfor automatic rheumatoid arthritis assessment which provides a joint space width measure. A hand joint model is proposed based on the accurate analysis of a X-ray finger joint image sample set. This model shows that the sclerosis and the lower bone are the main necessary features in order to perform a proper finger joint characterization. We propose sclerosis and lower bone detection methods as well as the experimental setup necessary for its performance assessment. Our characterization is used to propose and compute a joint space width score which is shown to be related to the different degrees of arthritis. This assertion is verified by comparing our proposed score with Sharp Van der Heijde score, confirming that the lower our score is the more advanced is the patient affection.
Keywords: Rheumatoid Arthritis; X-Ray; Hand Joint; Sclerosis; Sharp Van der Heijde
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Joan M. Nuñez, Jorge Bernal, F. Javier Sanchez, & Fernando Vilariño. (2013). "Blood Vessel Characterization in Colonoscopy Images to Improve Polyp Localization " In Proceedings of the International Conference on Computer Vision Theory and Applications (Vol. 1, pp. 162–171). SciTePress.
Abstract: This paper presents an approach to mitigate the contribution of blood vessels to the energy image used at different tasks of automatic colonoscopy image analysis. This goal is achieved by introducing a characterization of endoluminal scene objects which allows us to differentiate between the trace of 2-dimensional visual objects,such as vessels, and shades from 3-dimensional visual objects, such as folds. The proposed characterization is based on the influence that the object shape has in the resulting visual feature, and it leads to the development of a blood vessel attenuation algorithm. A database consisting of manually labelled masks was built in order to test the performance of our method, which shows an encouraging success in blood vessel mitigation while keeping other structures intact. Moreover, by extending our method to the only available polyp localization
algorithm tested on a public database, blood vessel mitigation proved to have a positive influence on the overall performance.
Keywords: Colonoscopy; Blood vessel; Linear features; Valley detection
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Fernando Vilariño, Stephan Ameling, Gerard Lacey, Stephen Patchett, & Hugh Mulcahy. (2009)." Eye Tracking Search Patterns in Expert and Trainee Colonoscopists: A Novel Method of Assessing Endoscopic Competency?" Gastrointestinal Endoscopy, 69(5), 370.
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Rozenn Dhayot, Fernando Vilariño, & Gerard Lacey. (2008). "Improving the Quality of Color Colonoscopy Videos " . EURASIP Journal on Image and Video Processing, 139429(1), 1–9.
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Stefan Ameling, Stephan Wirth, Dietrich Paulus, Gerard Lacey, & Fernando Vilariño. (2009)." Texture-based Polyp Detection in Colonoscopy" . Proc. BILDVERARBEITUNG FÜR DIE MEDIZIN, .
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Fernando Vilariño, & Gerard Lacey. (2009)." QUALITY ASSESSMENT IN COLONOSCOPY New challenges through computer vision-based systems" In in Proc. 3rd International Conference on Biomedical Electronics and Devices.
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Fernando Vilariño, Gerard Lacey, Jiang Zhou, Hugh Mulcahy, & Stephen Patchett. (2007)." Automatic Labeling of Colonoscopy Video for Cancer Detection" In In Proc. berian Conference, IbPRIA (pp. 290–297).
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Fernando Vilariño, & Enric Marti. (2008)." New didactic techniques in the EHES applying mobile technologies" .
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