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Author F. Javier Sanchez; Jordi Vitria edit  isbn
openurl 
  Title ViLi + : Extended Lisp for image Processing and Computer Vision. Type Conference Article
  Year 1994 Publication Progress in Image Analysis and Processing III Abbreviated Journal  
  Volume Issue Pages  
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  Abstract  
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  Corporate Author Thesis  
  Publisher World Scientific Place of Publication Editor S.Impedovo  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 981-02-1552-5 Medium  
  Area Expedition Conference  
  Notes MV;OR Approved no  
  Call Number BCNPCL @ bcnpcl @ SaV1994; IAM @ iam @ SaV1994 Serial 114  
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Author Jorge Bernal; Fernando Vilariño; F. Javier Sanchez edit   pdf
openurl 
  Title Feature Detectors and Feature Descriptors: Where We Are Now Type Report
  Year 2010 Publication CVC Technical Report Abbreviated Journal  
  Volume 154 Issue Pages  
  Keywords  
  Abstract Feature Detection and Feature Description are clearly nowadays topics. Many Computer Vision applications rely on the use of several of these techniques in order to extract the most significant aspects of an image so they can help in some tasks such as image retrieval, image registration, object recognition, object categorization and texture classification, among others. In this paper we define what Feature Detection and Description are and then we present an extensive collection of several methods in order to show the different techniques that are being used right now. The aim of this report is to provide a glimpse of what is being used currently in these fields and to serve as a starting point for future endeavours.  
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  ISSN ISBN Medium  
  Area 800 Expedition Conference  
  Notes MV; Approved no  
  Call Number Admin @ si @ BVS2010; IAM @ iam @ BVS2010 Serial 1348  
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Author F. Javier Sanchez; Jordi Vitria; Enric Marti edit  openurl
  Title Transformaciones Morfológicas de Polígonos Isotéticos Type Conference Article
  Year 1991 Publication Primer Congreso Español de Informática Gráfica. Abbreviated Journal  
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  Notes OR;IAM;MV Approved no  
  Call Number IAM @ iam @ SVM1991 Serial 1648  
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Author Jorge Bernal; Fernando Vilariño; F. Javier Sanchez edit   pdf
url  doi
isbn  openurl
  Title Towards Intelligent Systems for Colonoscopy Type Book Chapter
  Year 2011 Publication Colonoscopy Abbreviated Journal  
  Volume 1 Issue Pages 257-282  
  Keywords  
  Abstract In this chapter we present tools that can be used to build intelligent systems for colonoscopy.
The idea is, by using methods based on computer vision and artificial intelligence, add significant value to the colonoscopy procedure. Intelligent systems are being used to assist in other medical interventions
 
  Address (up)  
  Corporate Author Thesis  
  Publisher Intech Place of Publication Editor Paul Miskovitz  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-953-307-568-6 Medium  
  Area 800 Expedition Conference  
  Notes MV; Approved no  
  Call Number IAM @ iam @ BVS2011 Serial 1697  
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Author Jorge Bernal; F. Javier Sanchez; Fernando Vilariño edit   pdf
url  doi
openurl 
  Title Towards Automatic Polyp Detection with a Polyp Appearance Model Type Journal Article
  Year 2012 Publication Pattern Recognition Abbreviated Journal PR  
  Volume 45 Issue 9 Pages 3166-3182  
  Keywords Colonoscopy,PolypDetection,RegionSegmentation,SA-DOVA descriptot  
  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.  
  Address (up)  
  Corporate Author Thesis  
  Publisher Elsevier Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0031-3203 ISBN Medium  
  Area 800 Expedition Conference IbPRIA  
  Notes MV Approved no  
  Call Number Admin @ si @ BSV2012; IAM @ iam Serial 1997  
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Author Onur Ferhat; Fernando Vilariño; F. Javier Sanchez edit  url
openurl 
  Title A cheap portable eye-tracker solution for common setups. Type Journal Article
  Year 2014 Publication Journal of Eye Movement Research Abbreviated Journal JEMR  
  Volume 7 Issue 3 Pages 1-10  
  Keywords  
  Abstract We analyze the feasibility of a cheap eye-tracker where the hardware consists of a single webcam and a Raspberry Pi device. Our aim is to discover the limits of such a system and to see whether it provides an acceptable performance. We base our work on the open source Opengazer (Zielinski, 2013) and we propose several improvements to create a robust, real-time system which can work on a computer with 30Hz sampling rate. After assessing the accuracy of our eye-tracker in elaborated experiments involving 12 subjects under 4 different system setups, we install it on a Raspberry Pi to create a portable stand-alone eye-tracker which achieves 1.42° horizontal accuracy with 3Hz refresh rate for a building cost of 70 Euros.  
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  Area Expedition Conference  
  Notes Approved no  
  Call Number Admin @ si @ FVS2014 Serial 2435  
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Author Jorge Bernal; F. Javier Sanchez; Gloria Fernandez-Esparrach; Debora Gil; Cristina Rodriguez de Miguel; Fernando Vilariño edit   pdf
doi  openurl
  Title WM-DOVA Maps for Accurate Polyp Highlighting in Colonoscopy: Validation vs. Saliency Maps from Physicians Type Journal Article
  Year 2015 Publication Computerized Medical Imaging and Graphics Abbreviated Journal CMIG  
  Volume 43 Issue Pages 99-111  
  Keywords Polyp localization; Energy Maps; Colonoscopy; Saliency; Valley detection  
  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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  Series Volume Series Issue Edition  
  ISSN 0895-6111 ISBN Medium  
  Area Expedition Conference  
  Notes MV; IAM; 600.047; 600.060; 600.075 Approved no  
  Call Number Admin @ si @ BSF2015 Serial 2609  
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Author Carles Sanchez; Jorge Bernal; F. Javier Sanchez; T.Rosell; M.Diez; Debora Gil edit  doi
openurl 
  Title Towards On-line Quantification of Tracheal Stenosis from Videobronchoscopy Type Journal Article
  Year 2015 Publication International Journal of Computer Assisted Radiology and Surgery Abbreviated Journal IJCAR  
  Volume 10 Issue 6 Pages 935-945  
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  Notes IAM; MV; 600.075 Approved no  
  Call Number Admin @ si @ SBS2015a Serial 2611  
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Author Jorge Bernal; F. Javier Sanchez; Cristina Rodriguez; Gloria Fernandez-Esparrach edit  url
isbn  openurl
  Title Bulding up the future of colonoscopy: A synergy between clinicians and computer scientists Type Book Chapter
  Year 2015 Publication Colonoscopy and Colorectal Cancer Abbreviated Journal  
  Volume Issue Pages  
  Keywords Intelligent systems; Image properties; Validation; Clinical drawbacks; Endoluminal scene description  
  Abstract Recent advances in endoscopic technology have generated an increasing interest in strengthening the collaboration between clinicians and computers scientist to develop intelligent systems that can provide additional information to clinicians in the different stages of an intervention. The objective of this chapter is to identify clinical drawbacks of colonoscopy in order to define potential areas of collaboration. Once areas are defined, we present the challenges that colonoscopy images present in order computational methods to provide with meaningful output, including those related to image formation and acquisition, as they are proven to have an impact in the performance of an intelligent system. Finally, we also propose how to define validation frameworks in order to assess the performance of a given method, making an special emphasis on how databases should be created and annotated and which metrics should be used to evaluate systems correctly.  
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  Series Editor Series Title Abbreviated Series Title  
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  ISSN ISBN 978-953-51-2225-8 Medium  
  Area Expedition Conference  
  Notes MV Approved no  
  Call Number Admin @ si @ BSR2015 Serial 2624  
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Author Gloria Fernandez-Esparrach; Jorge Bernal; Cristina Rodriguez de Miguel; Debora Gil; Fernando Vilariño; H.Cordova; C.Sanchez-Montes; I.Araujo ; Maria Lopez-Ceron; J.Llach; F. Javier Sanchez edit   pdf
url  openurl
  Title Colonic polyps are correctly identified by a computer vision method using wm-dova energy maps Type Conference Article
  Year 2015 Publication Proceedings of 23 United European- UEG Week 2015 Abbreviated Journal  
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  Area Expedition Conference UEG  
  Notes MV; IAM; 600.075 Approved no  
  Call Number Admin @ si @ FBR2015 Serial 2732  
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Author Debora Gil; F. Javier Sanchez; Gloria Fernandez-Esparrach; Jorge Bernal edit   pdf
doi  openurl
  Title 3D Stable Spatio-temporal Polyp Localization in Colonoscopy Videos Type Book Chapter
  Year 2015 Publication Computer-Assisted and Robotic Endoscopy. Revised selected papers of Second International Workshop, CARE 2015, Held in Conjunction with MICCAI 2015 Abbreviated Journal  
  Volume 9515 Issue Pages 140-152  
  Keywords Colonoscopy, Polyp Detection, Polyp Localization, Region Extraction, Watersheds  
  Abstract Computational intelligent systems could reduce polyp miss rate in colonoscopy for colon cancer diagnosis and, thus, increase the efficiency of the procedure. One of the main problems of existing polyp localization methods is a lack of spatio-temporal stability in their response. We propose to explore the response of a given polyp localization across temporal windows in order to select
those image regions presenting the highest stable spatio-temporal response.
Spatio-temporal stability is achieved by extracting 3D watershed regions on the
temporal window. Stability in localization response is statistically determined by analysis of the variance of the output of the localization method inside each 3D region. We have explored the benefits of considering spatio-temporal stability in two different tasks: polyp localization and polyp detection. Experimental results indicate an average improvement of 21:5% in polyp localization and 43:78% in polyp detection.
 
  Address (up)  
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  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference CARE  
  Notes IAM; MV; 600.075 Approved no  
  Call Number Admin @ si @ GSF2015 Serial 2733  
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Author Joan M. Nuñez; Jorge Bernal; F. Javier Sanchez; Fernando Vilariño edit   pdf
doi  openurl
  Title Growing Algorithm for Intersection Detection (GRAID) in branching patterns Type Journal Article
  Year 2015 Publication Machine Vision and Applications Abbreviated Journal MVAP  
  Volume 26 Issue 2 Pages 387-400  
  Keywords Bifurcation ; Crossroad; Intersection ;Retina ; Vessel  
  Abstract Analysis of branching structures represents a very important task in fields such as medical diagnosis, road detection or biometrics. Detecting intersection landmarks Becomes crucial when capturing the structure of a branching pattern. We present a very simple geometrical model to describe intersections in branching structures based on two conditions: Bounded Tangency condition (BT) and Shortest Branch (SB) condition. The proposed model precisely sets a geometrical characterization of intersections and allows us to introduce a new unsupervised operator for intersection extraction. We propose an implementation that handles the consequences of digital domain operation that,unlike existing approaches, is not restricted to a particular scale and does not require the computation of the thinned pattern. The new proposal, as well as other existing approaches in the bibliography, are evaluated in a common framework for the first time. The performance analysis is based on two manually segmented image data sets: DRIVE retinal image database and COLON-VESSEL data set, a newly created data set of vascular content in colonoscopy frames. We have created an intersection landmark ground truth for each data set besides comparing our method in the only existing ground truth. Quantitative results confirm that we are able to outperform state-of-the-art performancelevels with the advantage that neither training nor parameter tuning is needed.  
  Address (up)  
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  Notes Approved no  
  Call Number Admin @ si @MBS2015 Serial 2777  
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Author Gloria Fernandez-Esparrach; Jorge Bernal; Maria Lopez-Ceron; Henry Cordova; Cristina Sanchez-Montes; Cristina Rodriguez de Miguel; F. Javier Sanchez edit   pdf
doi  openurl
  Title Exploring the clinical potential of an automatic colonic polyp detection method based on the creation of energy maps Type Journal Article
  Year 2016 Publication Endoscopy Abbreviated Journal END  
  Volume 48 Issue 9 Pages 837-842  
  Keywords  
  Abstract Background and aims: Polyp miss-rate is a drawback of colonoscopy that increases significantly in small polyps. We explored the efficacy of an automatic computer vision method for polyp detection.
Methods: Our method relies on a model that defines polyp boundaries as valleys of image intensity. Valley information is integrated into energy maps which represent the likelihood of polyp presence.
Results: In 24 videos containing polyps from routine colonoscopies, all polyps were detected in at least one frame. Mean values of the maximum of energy map were higher in frames with polyps than without (p<0.001). Performance improved in high quality frames (AUC= 0.79, 95%CI: 0.70-0.87 vs 0.75, 95%CI: 0.66-0.83). Using 3.75 as maximum threshold value, sensitivity and specificity for detection of polyps were 70.4% (95%CI: 60.3-80.8) and 72.4% (95%CI: 61.6-84.6), respectively.
Conclusion: Energy maps showed a good performance for colonic polyp detection. This indicates a potential applicability in clinical practice.
 
  Address (up)  
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  Notes MV; Approved no  
  Call Number Admin @ si @FBL2016 Serial 2778  
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Author David Vazquez; Jorge Bernal; F. Javier Sanchez; Gloria Fernandez-Esparrach; Antonio Lopez; Adriana Romero; Michal Drozdzal; Aaron Courville edit   pdf
openurl 
  Title A Benchmark for Endoluminal Scene Segmentation of Colonoscopy Images Type Conference Article
  Year 2017 Publication 31st International Congress and Exhibition on Computer Assisted Radiology and Surgery Abbreviated Journal  
  Volume Issue Pages  
  Keywords Deep Learning; Medical Imaging  
  Abstract Colorectal cancer (CRC) is the third cause of cancer death worldwide. Currently, the standard approach to reduce CRC-related mortality is to perform regular screening in search for polyps and colonoscopy is the screening tool of choice. The main limitations of this screening procedure are polyp miss-rate and inability to perform visual assessment of polyp malignancy. These drawbacks can be reduced by designing Decision Support Systems (DSS) aiming to help clinicians in the different stages of the procedure by providing endoluminal scene segmentation. Thus, in this paper, we introduce an extended benchmark of colonoscopy image, with the hope of establishing a new strong benchmark for colonoscopy image analysis research. We provide new baselines on this dataset by training standard fully convolutional networks (FCN) for semantic segmentation and significantly outperforming, without any further post-processing, prior results in endoluminal scene segmentation.  
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  ISSN ISBN Medium  
  Area Expedition Conference CARS  
  Notes ADAS; MV; 600.075; 600.085; 600.076; 601.281; 600.118 Approved no  
  Call Number ADAS @ adas @ VBS2017a Serial 2880  
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Author David Vazquez; Jorge Bernal; F. Javier Sanchez; Gloria Fernandez-Esparrach; Antonio Lopez; Adriana Romero; Michal Drozdzal; Aaron Courville edit   pdf
url  openurl
  Title A Benchmark for Endoluminal Scene Segmentation of Colonoscopy Images Type Journal Article
  Year 2017 Publication Journal of Healthcare Engineering Abbreviated Journal JHCE  
  Volume Issue Pages  
  Keywords Colonoscopy images; Deep Learning; Semantic Segmentation  
  Abstract Colorectal cancer (CRC) is the third cause of cancer death world-wide. Currently, the standard approach to reduce CRC-related mortality is to perform regular screening in search for polyps and colonoscopy is the screening tool of choice. The main limitations of this screening procedure are polyp miss- rate and inability to perform visual assessment of polyp malignancy. These drawbacks can be reduced by designing Decision Support Systems (DSS) aim- ing to help clinicians in the different stages of the procedure by providing endoluminal scene segmentation. Thus, in this paper, we introduce an extended benchmark of colonoscopy image segmentation, with the hope of establishing a new strong benchmark for colonoscopy image analysis research. The proposed dataset consists of 4 relevant classes to inspect the endolumninal scene, tar- geting different clinical needs. Together with the dataset and taking advantage of advances in semantic segmentation literature, we provide new baselines by training standard fully convolutional networks (FCN). We perform a compar- ative study to show that FCN significantly outperform, without any further post-processing, prior results in endoluminal scene segmentation, especially with respect to polyp segmentation and localization.  
  Address (up)  
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  Notes ADAS; MV; 600.075; 600.085; 600.076; 601.281; 600.118 Approved no  
  Call Number VBS2017b Serial 2940  
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Author Jorge Bernal; Nima Tajkbaksh; F. Javier Sanchez; Bogdan J. Matuszewski; Hao Chen; Lequan Yu; Quentin Angermann; Olivier Romain; Bjorn Rustad; Ilangko Balasingham; Konstantin Pogorelov; Sungbin Choi; Quentin Debard; Lena Maier-Hein; Stefanie Speidel; Danail Stoyanov; Patrick Brandao; Henry Cordova; Cristina Sanchez-Montes; Suryakanth R. Gurudu; Gloria Fernandez-Esparrach; Xavier Dray; Jianming Liang; Aymeric Histace edit   pdf
doi  openurl
  Title Comparative Validation of Polyp Detection Methods in Video Colonoscopy: Results from the MICCAI 2015 Endoscopic Vision Challenge Type Journal Article
  Year 2017 Publication IEEE Transactions on Medical Imaging Abbreviated Journal TMI  
  Volume 36 Issue 6 Pages 1231 - 1249  
  Keywords Endoscopic vision; Polyp Detection; Handcrafted features; Machine Learning; Validation Framework  
  Abstract Colonoscopy is the gold standard for colon cancer screening though still some polyps are missed, thus preventing early disease detection and treatment. Several computational systems have been proposed to assist polyp detection during colonoscopy but so far without consistent evaluation. The lack
of publicly available annotated databases has made it difficult to compare methods and to assess if they achieve performance levels acceptable for clinical use. The Automatic Polyp Detection subchallenge, conducted as part of the Endoscopic Vision Challenge (http://endovis.grand-challenge.org) at the international conference on Medical Image Computing and Computer Assisted
Intervention (MICCAI) in 2015, was an effort to address this need. In this paper, we report the results of this comparative evaluation of polyp detection methods, as well as describe additional experiments to further explore differences between methods. We define performance metrics and provide evaluation databases that allow comparison of multiple methodologies. Results show that convolutional neural networks (CNNs) are the state of the art. Nevertheless it is also demonstrated that combining different methodologies can lead to an improved overall performance.
 
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  Notes MV; 600.096; 600.075 Approved no  
  Call Number Admin @ si @ BTS2017 Serial 2949  
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Author F. Javier Sanchez; Jorge Bernal; Cristina Sanchez-Montes; Cristina Rodriguez de Miguel; Gloria Fernandez-Esparrach edit   pdf
url  openurl
  Title Bright spot regions segmentation and classification for specular highlights detection in colonoscopy videos Type Journal Article
  Year 2017 Publication Journal of Machine Vision and Applications Abbreviated Journal MVAP  
  Volume Issue Pages 1-20  
  Keywords Specular highlights; bright spot regions segmentation; region classification; colonoscopy  
  Abstract A novel specular highlights detection method in colonoscopy videos is presented. The method is based on a model of appearance dening specular
highlights as bright spots which are highly contrasted with respect to adjacent regions. Our approach proposes two stages; segmentation, and then classication
of bright spot regions. The former denes a set of candidate regions obtained through a region growing process with local maxima as initial region seeds. This process creates a tree structure which keeps track, at each growing iteration, of the region frontier contrast; nal regions provided depend on restrictions over contrast value. Non-specular regions are ltered through a classication stage performed by a linear SVM classier using model-based features from each region. We introduce a new validation database with more than 25; 000 regions along with their corresponding pixel-wise annotations. We perform a comparative study against other approaches. Results show that our method is superior to other approaches, with our segmented regions being
closer to actual specular regions in the image. Finally, we also present how our methodology can also be used to obtain an accurate prediction of polyp histology.
 
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  Notes MV; 600.096; 600.175 Approved no  
  Call Number Admin @ si @ SBS2017 Serial 2975  
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Author Jorge Bernal; Aymeric Histace; Marc Masana; Quentin Angermann; Cristina Sanchez-Montes; Cristina Rodriguez de Miguel; Maroua Hammami; Ana Garcia-Rodriguez; Henry Cordova; Olivier Romain; Gloria Fernandez-Esparrach; Xavier Dray; F. Javier Sanchez edit  openurl
  Title Polyp Detection Benchmark in Colonoscopy Videos using GTCreator: A Novel Fully Configurable Tool for Easy and Fast Annotation of Image Databases Type Conference Article
  Year 2018 Publication 32nd International Congress and Exhibition on Computer Assisted Radiology & Surgery Abbreviated Journal  
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  Area Expedition Conference CARS  
  Notes ISE; MV; 600.119 Approved no  
  Call Number Admin @ si @ BHM2018 Serial 3089  
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Author Jorge Bernal; Aymeric Histace; Marc Masana; Quentin Angermann; Cristina Sanchez Montes; Cristina Rodriguez de Miguel; Maroua Hammami; Ana Garcia Rodriguez; Henry Cordova; Olivier Romain; Gloria Fernandez Esparrach; Xavier Dray; F. Javier Sanchez edit   pdf
doi  openurl
  Title GTCreator: a flexible annotation tool for image-based datasets Type Journal Article
  Year 2019 Publication International Journal of Computer Assisted Radiology and Surgery Abbreviated Journal IJCAR  
  Volume 14 Issue 2 Pages 191–201  
  Keywords Annotation tool; Validation Framework; Benchmark; Colonoscopy; Evaluation  
  Abstract Abstract Purpose: Methodology evaluation for decision support systems for health is a time consuming-task. To assess performance of polyp detection
methods in colonoscopy videos, clinicians have to deal with the annotation
of thousands of images. Current existing tools could be improved in terms of
exibility and ease of use. Methods:We introduce GTCreator, a exible annotation tool for providing image and text annotations to image-based datasets.
It keeps the main basic functionalities of other similar tools while extending
other capabilities such as allowing multiple annotators to work simultaneously
on the same task or enhanced dataset browsing and easy annotation transfer aiming to speed up annotation processes in large datasets. Results: The
comparison with other similar tools shows that GTCreator allows to obtain
fast and precise annotation of image datasets, being the only one which offers
full annotation editing and browsing capabilites. Conclusions: Our proposed
annotation tool has been proven to be efficient for large image dataset annota-
tion, as well as showing potential of use in other stages of method evaluation
such as experimental setup or results analysis.
 
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  Notes MV; 600.096; 600.109; 600.119; 601.305 Approved no  
  Call Number Admin @ si @ BHM2019 Serial 3163  
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Author Cristina Sanchez Montes; F. Javier Sanchez; Jorge Bernal; Henry Cordova; Maria Lopez Ceron; Miriam Cuatrecasas; Cristina Rodriguez de Miguel; Ana Garcia Rodriguez; Rodrigo Garces Duran; Maria Pellise; Josep Llach; Gloria Fernandez Esparrach edit   pdf
doi  openurl
  Title Computer-aided Prediction of Polyp Histology on White-Light Colonoscopy using Surface Pattern Analysis Type Journal Article
  Year 2019 Publication Endoscopy Abbreviated Journal  
  Volume 51 Issue 3 Pages 261-265  
  Keywords  
  Abstract Background and study aims: To evaluate a new computational histology prediction system based on colorectal polyp textural surface patterns using high definition white light images.
Patients and methods: Textural elements (textons) were characterized according to their contrast with respect to the surface, shape and number of bifurcations, assuming that dysplastic polyps are associated with highly contrasted, large tubular patterns with some degree of bifurcation. Computer-aided diagnosis (CAD) was compared with pathological diagnosis and the diagnosis by the endoscopists using Kudo and NICE classification.
Results: Images of 225 polyps were evaluated (142 dysplastic and 83 non-dysplastic). CAD system correctly classified 205 (91.1%) polyps, 131/142 (92.3%) dysplastic and 74/83 (89.2%) non-dysplastic. For the subgroup of 100 diminutive (<5 mm) polyps, CAD correctly classified 87 (87%) polyps, 43/50 (86%) dysplastic and 44/50 (88%) non-dysplastic. There were not statistically significant differences in polyp histology prediction based on CAD system and on endoscopist assessment.
Conclusion: A computer vision system based on the characterization of the polyp surface in the white light accurately predicts colorectal polyp histology.
 
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  Notes MV; 600.096; 600.119; 600.075 Approved no  
  Call Number Admin @ si @ SSB2019 Serial 3164  
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Author Carles Sanchez;F. Javier Sanchez; Antoni Rosell; Debora Gil edit   pdf
url  doi
isbn  openurl
  Title An illumination model of the trachea appearance in videobronchoscopy images Type Book Chapter
  Year 2012 Publication Image Analysis and Recognition Abbreviated Journal LNCS  
  Volume 7325 Issue Pages 313-320  
  Keywords Bronchoscopy, tracheal ring, stenosis assesment, trachea appearance model, segmentation  
  Abstract Videobronchoscopy is a medical imaging technique that allows interactive navigation inside the respiratory pathways. This imaging modality provides realistic images and allows non-invasive minimal intervention procedures. Tracheal procedures are routinary interventions that require assessment of the percentage of obstructed pathway for injury (stenosis) detection. Visual assessment in videobronchoscopic sequences requires high expertise of trachea anatomy and is prone to human error.
This paper introduces an automatic method for the estimation of steneosed trachea percentage reduction in videobronchoscopic images. We look for tracheal rings , whose deformation determines the degree of obstruction. For ring extraction , we present a ring detector based on an illumination and appearance model. This model allows us to parametrise the ring detection. Finally, we can infer optimal estimation parameters for any video resolution.
 
  Address (up) Aveiro, Portugal  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-31297-7 Medium  
  Area 800 Expedition Conference ICIAR  
  Notes MV;IAM Approved no  
  Call Number IAM @ iam @ SSR2012 Serial 1898  
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Author Quentin Angermann; Jorge Bernal; Cristina Sanchez-Montes; Maroua Hammami; Gloria Fernandez-Esparrach; Xavier Dray; Olivier Romain; F. Javier Sanchez; Aymeric Histace edit