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Author Ana Maria Ares; Jorge Bernal; Maria Jesus Nozal; F. Javier Sanchez; Jose Bernal edit  url
doi  openurl
  Title Results of the use of Kahoot! gamification tool in a course of Chemistry Type Conference Article
  Year 2018 Publication 4th International Conference on Higher Education Advances Abbreviated Journal  
  Volume Issue Pages 1215-1222  
  Keywords  
  Abstract The present study examines the use of Kahoot! as a gamification tool to explore mixed learning strategies. We analyze its use in two different groups of a theoretical subject of the third course of the Degree in Chemistry. An empirical-analytical methodology was used using Kahoot! in two different groups of students, with different frequencies. The academic results of these two group of students were compared between them and with those obtained in the previous course, in which Kahoot! was not employed, with the aim of measuring the evolution in the students´ knowledge. The results showed, in all cases, that the use of Kahoot! has led to a significant increase in the overall marks, and in the number of students who passed the subject. Moreover, some differences were also observed in students´ academic performance according to the group. Finally, it can be concluded that the use of a gamification tool (Kahoot!) in a university classroom had generally improved students´ learning and marks, and that this improvement is more prevalent in those students who have achieved a better Kahoot! performance.  
  Address Valencia; June 2018  
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  Notes MV; no proj Approved no  
  Call Number Admin @ si @ ABN2018 Serial (down) 3246  
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Author F. Javier Sanchez; Jorge Bernal edit  url
doi  openurl
  Title Use of Software Tools for Real-time Monitoring of Learning Processes: Application to Compilers subject Type Conference Article
  Year 2018 Publication 4th International Conference of Higher Education Advances Abbreviated Journal  
  Volume Issue Pages 1359-1366  
  Keywords Monitoring; Evaluation tool; Gamification; Student motivation  
  Abstract The effective implementation of the Higher European Education Area has meant a change regarding the focus of the learning process, being now the student at its very center. This shift of focus requires a strong involvement and fluent communication between teachers and students to succeed. Considering the difficulties associated to motivate students to take a more active role in the learning process, we explore how the use of a software tool can help both actors to improve the learning experience. We present a tool that can help students to obtain instantaneous feedback with respect to their progress in the subject as well as providing teachers with useful information about the evolution of knowledge acquisition with respect to each of the subject areas. We compare the performance achieved by students in two academic years: results show an improvement in overall performance which, after observing graphs provided by our tool, can be associated to an increase in students interest in the subject.  
  Address Valencia; June 2018  
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  Area Expedition Conference HEAD  
  Notes MV; no proj Approved no  
  Call Number Admin @ si @ SaB2018 Serial (down) 3165  
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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 (down) 3164  
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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 (down) 3163  
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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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  Notes ISE; MV; 600.119 Approved no  
  Call Number Admin @ si @ BHM2018 Serial (down) 3089  
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Author Cristina Sanchez-Montes; F. Javier Sanchez; Cristina Rodriguez de Miguel; Henry Cordova; Jorge Bernal; Maria Lopez-Ceron; Josep Llach; Gloria Fernandez-Esparrach edit   pdf
openurl 
  Title Histological Prediction Of Colonic Polyps By Computer Vision. Preliminary Results Type Conference Article
  Year 2017 Publication 25th United European Gastroenterology Week Abbreviated Journal  
  Volume Issue Pages  
  Keywords polyps; histology; computer vision  
  Abstract during colonoscopy, clinicians perform visual inspection of the polyps to predict histology. Kudo’s pit pattern classification is one of the most commonly used for optical diagnosis. These surface patterns present a contrast with respect to their neighboring regions and they can be considered as bright regions in the image that can attract the attention of computational methods.  
  Address Barcelona; October 2017  
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  Area Expedition Conference ESGE  
  Notes MV; no menciona Approved no  
  Call Number Admin @ si @ SSR2017 Serial (down) 2979  
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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  openurl
  Title Clinical Usability Quantification Of a Real-Time Polyp Detection Method In Videocolonoscopy Type Conference Article
  Year 2017 Publication 25th United European Gastroenterology Week Abbreviated Journal  
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  Address Barcelona, October 2017  
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  Notes MV; no menciona Approved no  
  Call Number Admin @ si @ ABS2017c Serial (down) 2978  
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Author Quentin Angermann; Jorge Bernal; Cristina Sanchez-Montes; Gloria Fernandez-Esparrach; Xavier Gray; Olivier Romain; F. Javier Sanchez; Aymeric Histace edit   pdf
openurl 
  Title Towards Real-Time Polyp Detection in Colonoscopy Videos: Adapting Still Frame-Based Methodologies for Video Sequences Analysis Type Conference Article
  Year 2017 Publication 4th International Workshop on Computer Assisted and Robotic Endoscopy Abbreviated Journal  
  Volume Issue Pages 29-41  
  Keywords Polyp detection; colonoscopy; real time; spatio temporal coherence  
  Abstract Colorectal cancer is the second cause of cancer death in United States: precursor lesions (polyps) detection is key for patient survival. Though colonoscopy is the gold standard screening tool, some polyps are still missed. Several computational systems have been proposed but none of them are used in the clinical room mainly due to computational constraints. Besides, most of them are built over still frame databases, decreasing their performance on video analysis due to the lack of output stability and not coping with associated variability on image quality and polyp appearance. We propose a strategy to adapt these methods to video analysis by adding a spatio-temporal stability module and studying a combination of features to capture polyp appearance variability. We validate our strategy, incorporated on a real-time detection method, on a public video database. Resulting method detects all
polyps under real time constraints, increasing its performance due to our
adaptation strategy.
 
  Address Quebec; Canada; September 2017  
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  Area Expedition Conference CARE  
  Notes MV; 600.096; 600.075 Approved no  
  Call Number Admin @ si @ ABS2017b Serial (down) 2977  
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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 (down) 2975  
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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 (down) 2949  
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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   pdf
openurl 
  Title Real-Time Polyp Detection in Colonoscopy Videos: A Preliminary Study For Adapting Still Frame-based Methodology To Video Sequences Analysis Type Conference Article
  Year 2017 Publication 31st International Congress and Exhibition on Computer Assisted Radiology and Surgery Abbreviated Journal  
  Volume Issue Pages  
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  Abstract  
  Address Barcelona; Spain; June 2017  
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  Series Editor Series Title Abbreviated Series Title  
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  Area Expedition Conference CARS  
  Notes MV; no menciona Approved no  
  Call Number Admin @ si @ ABS2017 Serial (down) 2947  
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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.  
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  Notes ADAS; MV; 600.075; 600.085; 600.076; 601.281; 600.118 Approved no  
  Call Number VBS2017b Serial (down) 2940  
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Author Carles Sanchez; Debora Gil; Jorge Bernal; F. Javier Sanchez; Marta Diez-Ferrer; Antoni Rosell edit  openurl
  Title Navigation Path Retrieval from Videobronchoscopy using Bronchial Branches Type Conference Article
  Year 2016 Publication 19th International Conference on Medical Image Computing and Computer Assisted Intervention Workshops Abbreviated Journal  
  Volume 9401 Issue Pages 62-70  
  Keywords Bronchoscopy navigation; Lumen center; Brochial branches; Navigation path; Videobronchoscopy  
  Abstract Bronchoscopy biopsy can be used to diagnose lung cancer without risking complications of other interventions like transthoracic needle aspiration. During bronchoscopy, the clinician has to navigate through the bronchial tree to the target lesion. A main drawback is the difficulty to check whether the exploration is following the correct path. The usual guidance using fluoroscopy implies repeated radiation of the clinician, while alternative systems (like electromagnetic navigation) require specific equipment that increases intervention costs. We propose to compute the navigated path using anatomical landmarks extracted from the sole analysis of videobronchoscopy images. Such landmarks allow matching the current exploration to the path previously planned on a CT to indicate clinician whether the planning is being correctly followed or not. We present a feasibility study of our landmark based CT-video matching using bronchoscopic videos simulated on a virtual bronchoscopy interactive interface.  
  Address Quebec; Canada; September 2016  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference MICCAI-W  
  Notes IAM; MV; 600.060; 600.075 Approved no  
  Call Number Admin @ si @ SGB2016 Serial (down) 2885  
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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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  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 (down) 2880  
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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.
 
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  Notes MV; Approved no  
  Call Number Admin @ si @FBL2016 Serial (down) 2778  
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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.  
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  Call Number Admin @ si @MBS2015 Serial (down) 2777  
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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.
 
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  Series Editor Series Title Abbreviated Series Title LNCS  
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  Notes IAM; MV; 600.075 Approved no  
  Call Number Admin @ si @ GSF2015 Serial (down) 2733  
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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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  Notes MV; IAM; 600.075 Approved no  
  Call Number Admin @ si @ FBR2015 Serial (down) 2732  
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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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  ISSN ISBN 978-953-51-2225-8 Medium  
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  Notes MV Approved no  
  Call Number Admin @ si @ BSR2015 Serial (down) 2624  
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Author Carles Sanchez; Jorge Bernal; F. Javier Sanchez; Marta Diez; Antoni Rosell; Debora Gil edit  openurl
  Title Towards On-line Quantification of Tracheal Stenosis from Videobronchoscopy Type Conference Article
  Year 2015 Publication 6th International Conference on Information Processing in Computer-Assisted Interventions IPCAI2015 Abbreviated Journal  
  Volume 10 Issue 6 Pages 935-945  
  Keywords  
  Abstract PURPOSE:
Lack of objective measurement of tracheal obstruction degree has a negative impact on the chosen treatment prone to lead to unnecessary repeated explorations and other scanners. Accurate computation of tracheal stenosis in videobronchoscopy would constitute a breakthrough for this noninvasive technique and a reduction in operation cost for the public health service.
METHODS:
Stenosis calculation is based on the comparison of the region delimited by the lumen in an obstructed frame and the region delimited by the first visible ring in a healthy frame. We propose a parametric strategy for the extraction of lumen and tracheal ring regions based on models of their geometry and appearance that guide a deformable model. To ensure a systematic applicability, we present a statistical framework to choose optimal parametric values and a strategy to choose the frames that minimize the impact of scope optical distortion.
RESULTS:
Our method has been tested in 40 cases covering different stenosed tracheas. Experiments report a non- clinically relevant [Formula: see text] of discrepancy in the calculated stenotic area and a computational time allowing online implementation in the operating room.
CONCLUSIONS:
Our methodology allows reliable measurements of airway narrowing in the operating room. To fully assess its clinical impact, a prospective clinical trial should be done.
 
  Address Barcelona; Spain; June 2015  
  Corporate Author Thesis  
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  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference IPCAI  
  Notes IAM; MV; 600.075 Approved no  
  Call Number Admin @ si @ SBS2015b Serial (down) 2613  
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Author Carles Sanchez; Debora Gil; R. Tazi; Jorge Bernal; Y. Ruiz; L. Planas; F. Javier Sanchez; Antoni Rosell edit  openurl
  Title Quasi-real time digital assessment of Central Airway Obstruction Type Conference Article
  Year 2015 Publication 3rd European congress for bronchology and interventional pulmonology ECBIP2015 Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Barcelona; Spain; April 2015  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ECBIP  
  Notes IAM; MV; 600.075 Approved no  
  Call Number SGT2015 Serial (down) 2612  
Permanent link to this record
 

 
Author Carles Sanchez; Jorge Bernal; F. Javier Sanchez; T.Rosell; M.Diez; Debora Gil edit  doi
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