|
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.
|
|
|
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
|
|
|
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.
|
|
|
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
|
|
|
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.
|
|
|
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.
|
|
|
Stefan Ameling, Stephan Wirth, Dietrich Paulus, Gerard Lacey, & Fernando Vilariño. (2009)." Texture-based Polyp Detection in Colonoscopy" . Proc. BILDVERARBEITUNG FÜR DIE MEDIZIN, .
|
|
|
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.
|
|
|
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).
|
|
|
Onur Ferhat, Arcadi Llanza, & Fernando Vilariño. (2015). "A Feature-Based Gaze Estimation Algorithm for Natural Light Scenarios " In Pattern Recognition and Image Analysis, Proceedings of 7th Iberian Conference , ibPRIA 2015 (Vol. 9117, pp. 569–576). Springer International Publishing.
Abstract: We present an eye tracking system that works with regular webcams. We base our work on open source CVC Eye Tracker [7] and we propose a number of improvements and a novel gaze estimation method. The new method uses features extracted from iris segmentation and it does not fall into the traditional categorization of appearance–based/model–based methods. Our experiments show that our approach reduces the gaze estimation errors by 34 % in the horizontal direction and by 12 % in the vertical direction compared to the baseline system.
Keywords: Eye tracking; Gaze estimation; Natural light; Webcam
|
|
|
Onur Ferhat, Arcadi Llanza, & Fernando Vilariño. (2015)." Gaze interaction for multi-display systems using natural light eye-tracker" In 2nd International Workshop on Solutions for Automatic Gaze Data Analysis.
|
|
|
Dan Norton, Fernando Vilariño, & Onur Ferhat. (2015)." Memory Field – Creative Engagement in Digital Collections" In Internet Librarian International Conference.
Abstract: “Memory Fields” is a trans-disciplinary project aiming at the (re)valorisation of digital collections.Its main deliverable is an interface for a dual screen installation, used to access and mix the public library digital collections. The collections being used in this case are a collection of digitised posters from the Spanish Civil War, belonging to the Arxiu General de Catalunya, and a collection of field recordings made by Dan Norton. The system generates visualisations, and the images and sounds are mixed together using narrative primitives of video dj. Users contribute to the digital collections by adding personal memories and observations. The comments and recollections appear as flowers growing in a “memory field” and memories remain public in a Twitter feed (@Memoryfields).
|
|
|
Fernando Vilariño. (2015)." Computer Vision and Performing Arts" In Korean Scholars of Marketing Science.
|
|
|
Santiago Segui, Laura Igual, Fernando Vilariño, Petia Radeva, Carolina Malagelada, Fernando Azpiroz, et al. (2008). "Diagnostic System for Intestinal Motility Disfunctions Using Video Capsule Endoscopy " In and J.K. Tsotsos M. V. A. Gasteratos (Ed.), Computer Vision Systems. 6th International (Vol. 5008, 251–260). Berlin Heidelberg: Springer-Verlag.
Abstract: Wireless Video Capsule Endoscopy is a clinical technique consisting of the analysis of images from the intestine which are pro- vided by an ingestible device with a camera attached to it. In this paper we propose an automatic system to diagnose severe intestinal motility disfunctions using the video endoscopy data. The system is based on the application of computer vision techniques within a machine learn- ing framework in order to obtain the characterization of diverse motil- ity events from video sequences. We present experimental results that demonstrate the effectiveness of the proposed system and compare them with the ground-truth provided by the gastroenterologists.
|
|