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Author |
Jorge Bernal; F. Javier Sanchez; Fernando Vilariño |
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Title |
Towards Automatic Polyp Detection with a Polyp Appearance Model |
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Journal Article |
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Year |
2012 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
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Volume  |
45 |
Issue |
9 |
Pages |
3166-3182 |
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Keywords |
Colonoscopy,PolypDetection,RegionSegmentation,SA-DOVA descriptot |
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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. |
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Elsevier |
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0031-3203 |
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800 |
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IbPRIA |
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Notes |
MV;SIAI |
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no |
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Admin @ si @ BSV2012; IAM @ iam |
Serial |
1997 |
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Author |
Jorge Bernal; F. Javier Sanchez; Gloria Fernandez Esparrach; Debora Gil; Cristina Rodriguez de Miguel; Fernando Vilariño |
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Title |
WM-DOVA Maps for Accurate Polyp Highlighting in Colonoscopy: Validation vs. Saliency Maps from Physicians |
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Journal Article |
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Year |
2015 |
Publication |
Computerized Medical Imaging and Graphics |
Abbreviated Journal |
CMIG |
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Volume |
43 |
Issue |
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Pages |
99-111 |
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Keywords |
Polyp localization; Energy Maps; Colonoscopy; Saliency; Valley detection |
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Abstract |
We introduce in this paper a novel polyp localization method for colonoscopy videos. Our method is based on a model of appearance for polyps which defines polyp boundaries in terms of valley information. We propose the integration of valley information in a robust way fostering complete, concave and continuous boundaries typically associated to polyps. This integration is done by using a window of radial sectors which accumulate valley information to create WMDOVA1 energy maps related with the likelihood of polyp presence. We perform a double validation of our maps, which include the introduction of two new databases, including the first, up to our knowledge, fully annotated database with clinical metadata associated. First we assess that the highest value corresponds with the location of the polyp in the image. Second, we show that WM-DOVA energy maps can be comparable with saliency maps obtained from physicians' fixations obtained via an eye-tracker. Finally, we prove that our method outperforms state-of-the-art computational saliency results. Our method shows good performance, particularly for small polyps which are reported to be the main sources of polyp miss-rate, which indicates the potential applicability of our method in clinical practice. |
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0895-6111 |
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MV; IAM; 600.047; 600.060; 600.075;SIAI |
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no |
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Admin @ si @ BSF2015 |
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2609 |
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Author |
Cristina Sanchez Montes; Jorge Bernal; Ana Garcia Rodriguez; Henry Cordova; Gloria Fernandez Esparrach |
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Title |
Revisión de métodos computacionales de detección y clasificación de pólipos en imagen de colonoscopia |
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Journal Article |
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Year |
2020 |
Publication |
Gastroenterología y Hepatología |
Abbreviated Journal |
GH |
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43 |
Issue |
4 |
Pages |
222-232 |
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Computer-aided diagnosis (CAD) is a tool with great potential to help endoscopists in the tasks of detecting and histologically classifying colorectal polyps. In recent years, different technologies have been described and their potential utility has been increasingly evidenced, which has generated great expectations among scientific societies. However, most of these works are retrospective and use images of different quality and characteristics which are analysed off line. This review aims to familiarise gastroenterologists with computational methods and the particularities of endoscopic imaging, which have an impact on image processing analysis. Finally, the publicly available image databases, needed to compare and confirm the results obtained with different methods, are presented. |
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MV; |
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no |
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Admin @ si @ SBG2020 |
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3404 |
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Author |
David Masip; Agata Lapedriza; Jordi Vitria |
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Title |
Boosted Online Learning for Face Recognition |
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Journal Article |
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Year |
2009 |
Publication |
IEEE Transactions on Systems, Man and Cybernetics part B |
Abbreviated Journal |
TSMCB |
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39 |
Issue |
2 |
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530–538 |
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Face recognition applications commonly suffer from three main drawbacks: a reduced training set, information lying in high-dimensional subspaces, and the need to incorporate new people to recognize. In the recent literature, the extension of a face classifier in order to include new people in the model has been solved using online feature extraction techniques. The most successful approaches of those are the extensions of the principal component analysis or the linear discriminant analysis. In the current paper, a new online boosting algorithm is introduced: a face recognition method that extends a boosting-based classifier by adding new classes while avoiding the need of retraining the classifier each time a new person joins the system. The classifier is learned using the multitask learning principle where multiple verification tasks are trained together sharing the same feature space. The new classes are added taking advantage of the structure learned previously, being the addition of new classes not computationally demanding. The present proposal has been (experimentally) validated with two different facial data sets by comparing our approach with the current state-of-the-art techniques. The results show that the proposed online boosting algorithm fares better in terms of final accuracy. In addition, the global performance does not decrease drastically even when the number of classes of the base problem is multiplied by eight. |
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1083–4419 |
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OR;MV |
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BCNPCL @ bcnpcl @ MLV2009 |
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1155 |
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Author |
Fadi Dornaika; Bogdan Raducanu |
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Title |
Three-Dimensional Face Pose Detection and Tracking Using Monocular Videos: Tool and Application |
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Journal Article |
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Year |
2009 |
Publication |
IEEE Transactions on Systems, Man and Cybernetics part B |
Abbreviated Journal |
TSMCB |
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Volume |
39 |
Issue |
4 |
Pages |
935–944 |
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Recently, we have proposed a real-time tracker that simultaneously tracks the 3-D head pose and facial actions in monocular video sequences that can be provided by low quality cameras. This paper has two main contributions. First, we propose an automatic 3-D face pose initialization scheme for the real-time tracker by adopting a 2-D face detector and an eigenface system. Second, we use the proposed methods-the initialization and tracking-for enhancing the human-machine interaction functionality of an AIBO robot. More precisely, we show how the orientation of the robot's camera (or any active vision system) can be controlled through the estimation of the user's head pose. Applications based on head-pose imitation such as telepresence, virtual reality, and video games can directly exploit the proposed techniques. Experiments on real videos confirm the robustness and usefulness of the proposed methods. |
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OR;MV |
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BCNPCL @ bcnpcl @ DoR2009a |
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1218 |
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