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Author Carles Sanchez; Debora Gil; Antoni Rosell; Albert Andaluz; F. Javier Sanchez edit   pdf
isbn  openurl
  Title Segmentation of Tracheal Rings in Videobronchoscopy combining Geometry and Appearance Type Conference Article
  Year 2013 Publication Proceedings of the International Conference on Computer Vision Theory and Applications Abbreviated Journal  
  Volume 1 Issue Pages 153--161  
  Keywords (down) Video-bronchoscopy, tracheal ring segmentation, trachea geometric and appearance model  
  Abstract Videobronchoscopy is a medical imaging technique that allows interactive navigation inside the respiratory pathways and minimal invasive interventions. Tracheal procedures are ordinary interventions that require measurement of the percentage of obstructed pathway for injury (stenosis) assessment. Visual assessment of stenosis in videobronchoscopic sequences requires high expertise of trachea anatomy and is prone to human error. Accurate detection of tracheal rings is the basis for automated estimation of the size of stenosed trachea. Processing of videobronchoscopic images acquired at the operating room is a challenging task due to the wide range of artifacts and acquisition conditions. We present a model of the geometric-appearance of tracheal rings for its detection in videobronchoscopic videos. Experiments on sequences acquired at the operating room, show a performance close to inter-observer variability  
  Address Barcelona; February 2013  
  Corporate Author Thesis  
  Publisher SciTePress Place of Publication Portugal Editor Sebastiano Battiato and José Braz  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-989-8565-47-1 Medium  
  Area 800 Expedition Conference VISAPP  
  Notes IAM;MV; 600.044; 600.047; 600.060; 605.203 Approved no  
  Call Number IAM @ iam @ SGR2013 Serial 2123  
Permanent link to this record
 

 
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 (down) 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.
 
  Address  
  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  
  Notes MV; 600.096; 600.175 Approved no  
  Call Number Admin @ si @ SBS2017 Serial 2975  
Permanent link to this record
 

 
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 (down) 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  
  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 ESGE  
  Notes MV; no menciona Approved no  
  Call Number Admin @ si @ SSR2017 Serial 2979  
Permanent link to this record
 

 
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 (down) 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.  
  Address  
  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 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  
Permanent link to this record
 

 
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 (down) 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  
  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 CARE  
  Notes MV; 600.096; 600.075 Approved no  
  Call Number Admin @ si @ ABS2017b Serial 2977  
Permanent link to this record
 

 
Author Jorge Bernal; F. Javier Sanchez; Fernando Vilariño edit   pdf
url  isbn
openurl 
  Title Depth of Valleys Accumulation Algorithm for Object Detection Type Conference Article
  Year 2011 Publication 14th Congrès Català en Intel·ligencia Artificial Abbreviated Journal  
  Volume 1 Issue 1 Pages 71-80  
  Keywords (down) Object Recognition, Object Region Identification, Image Analysis, Image Processing  
  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.  
  Address Lleida  
  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 978-1-60750-841-0 Medium  
  Area 800 Expedition Conference CCIA  
  Notes MV Approved no  
  Call Number IAM @ iam @ BSV2011b Serial 1699  
Permanent link to this record
 

 
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 (down) 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  
  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 HEAD  
  Notes MV; no proj Approved no  
  Call Number Admin @ si @ SaB2018 Serial 3165  
Permanent link to this record
 

 
Author Jorge Bernal; F. Javier Sanchez; Fernando Vilariño edit   pdf
url  openurl
  Title Current Challenges on Polyp Detection in Colonoscopy Videos: From Region Segmentation to Region Classification. a Pattern Recognition-based Approach.ased Approach Type Conference Article
  Year 2011 Publication 2nd International Workshop on Medical Image Analysis and Descriptionfor Diagnosis Systems Abbreviated Journal  
  Volume Issue Pages 62-71  
  Keywords (down) Medical Imaging, Colonoscopy, Pattern Recognition, Segmentation, Polyp Detection, Region Description, Machine Learning, Real-time.  
  Abstract In this paper we present our approach on real-time polyp detection in colonoscopy videos. Our method consists of three stages: Image Segmentation, Region Description and Image Classification. Taking into account the constraints of our project, we introduce our segmentation system that is based on the model of appearance of the polyp that we have defined after observing real videos from colonoscopy processes. The output of this stage will ideally be a low number of regions of which one of them should cover the whole polyp region (if there is one in the image). This regions will be described in terms of features and, as a result of a machine learning schema, classified based on the values that they have for the several features that we will use on their description. Although we are still on the early stages of the project, we present some preliminary segmentation results that indicates that we are going in a good direction.  
  Address Rome, Italy  
  Corporate Author Thesis  
  Publisher SciTePress Place of Publication Editor Djemal, Khalifa  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area 800 Expedition Conference MIAD  
  Notes MV; Approved no  
  Call Number IAM @ iam @ BSV2011a Serial 1695  
Permanent link to this record
 

 
Author Sergio Vera; Debora Gil; Agnes Borras; F. Javier Sanchez; Frederic Perez; Marius G. Linguraru ; Miguel A. Gonzalez Ballester edit   pdf
doi  isbn
openurl 
  Title Computation and Evaluation of Medial Surfaces for Shape Representation of Abdominal Organs Type Book Chapter
  Year 2012 Publication Workshop on Computational and Clinical Applications in Abdominal Imaging Abbreviated Journal  
  Volume 7029 Issue Pages 223–230  
  Keywords (down) medial manifolds, abdomen.  
  Abstract Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Existing methods show excellent results when applied to 2D
objects, but their quality drops across dimensions. This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial
manifolds that avoid degenerated medial axis segments; second, we introduce an energy based method which performs independently of the dimension. We evaluate quantitatively the performance of our
method with respect to existing approaches, by applying them to synthetic shapes of known medial geometry. Finally, we show results on shape representation of multiple abdominal organs,
exploring the use of medial manifolds for the representation of multi-organ relations.
 
  Address Toronto; Canada;  
  Corporate Author Thesis  
  Publisher Springer Link Place of Publication Berlin Editor H. Yoshida et al  
  Language English Summary Language English Original Title  
  Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-28556-1 Medium  
  Area Expedition Conference ABDI  
  Notes IAM;MV Approved no  
  Call Number IAM @ iam @ VGB2012 Serial 1834  
Permanent link to this record
 

 
Author Carles Sanchez; Jorge Bernal; Debora Gil; F. Javier Sanchez edit   pdf
doi  isbn
openurl 
  Title On-line lumen centre detection in gastrointestinal and respiratory endoscopy Type Conference Article
  Year 2013 Publication Second International Workshop Clinical Image-Based Procedures Abbreviated Journal  
  Volume 8361 Issue Pages 31-38  
  Keywords (down) Lumen centre detection; Bronchoscopy; Colonoscopy  
  Abstract We present in this paper a novel lumen centre detection for gastrointestinal and respiratory endoscopic images. The proposed method is based on the appearance and geometry of the lumen, which we defined as the darkest image region which centre is a hub of image gradients. Experimental results validated on the first public annotated gastro-respiratory database prove the reliability of the method for a wide range of images (with precision over 95 %).  
  Address Nagoya; Japan; September 2013  
  Corporate Author Thesis  
  Publisher Springer International Publishing Place of Publication Editor Erdt, Marius and Linguraru, Marius George and Oyarzun Laura, Cristina and Shekhar, Raj and Wesarg, Stefan and González Ballester, Miguel Angel and Drechsler, Klaus  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-319-05665-4 Medium  
  Area 800 Expedition Conference CLIP  
  Notes MV; IAM; 600.047; 600.044; 600.060 Approved no  
  Call Number Admin @ si @ SBG2013 Serial 2302  
Permanent link to this record
 

 
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 (down) 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.  
  Address  
  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 978-953-51-2225-8 Medium  
  Area Expedition Conference  
  Notes MV Approved no  
  Call Number Admin @ si @ BSR2015 Serial 2624  
Permanent link to this record
 

 
Author Jorge Bernal; Joan M. Nuñez; F. Javier Sanchez; Fernando Vilariño edit   pdf
doi  openurl
  Title Polyp Segmentation Method in Colonoscopy Videos by means of MSA-DOVA Energy Maps Calculation Type Conference Article
  Year 2014 Publication 3rd MICCAI Workshop on Clinical Image-based Procedures: Translational Research in Medical Imaging Abbreviated Journal  
  Volume 8680 Issue Pages 41-49  
  Keywords (down) Image segmentation; Polyps; Colonoscopy; Valley information; Energy maps  
  Abstract In this paper we present a novel polyp region segmentation method for colonoscopy videos. Our method uses valley information associated to polyp boundaries in order to provide an initial segmentation. This first segmentation is refined to eliminate boundary discontinuities caused by image artifacts or other elements of the scene. Experimental results over a publicly annotated database show that our method outperforms both general and specific segmentation methods by providing more accurate regions rich in polyp content. We also prove how image preprocessing is needed to improve final polyp region segmentation.  
  Address Boston; USA; September 2014  
  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 CLIP  
  Notes MV; 600.060; 600.044; 600.047 Approved no  
  Call Number Admin @ si @ BNS2014 Serial 2502  
Permanent link to this record
 

 
Author Jorge Bernal; Debora Gil; Carles Sanchez; F. Javier Sanchez edit   pdf
doi  isbn
openurl 
  Title Discarding Non Informative Regions for Efficient Colonoscopy Image Analysis Type Conference Article
  Year 2014 Publication 1st MICCAI Workshop on Computer-Assisted and Robotic Endoscopy Abbreviated Journal  
  Volume 8899 Issue Pages 1-10  
  Keywords (down) Image Segmentation; Polyps, Colonoscopy; Valley Information; Energy Maps  
  Abstract In this paper we present a novel polyp region segmentation method for colonoscopy videos. Our method uses valley information associated to polyp boundaries in order to provide an initial segmentation. This first segmentation is refined to eliminate boundary discontinuities caused by image artifacts or other elements of the scene. Experimental results over a publicly annotated database show that our method outperforms both general and specific segmentation methods by providing more accurate regions rich in polyp content. We also prove how image preprocessing is needed to improve final polyp region segmentation.  
  Address Boston; USA; September 2014  
  Corporate Author Thesis  
  Publisher Springer International Publishing Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-319-13409-3 Medium  
  Area Expedition Conference CARE  
  Notes MV; IAM; 600.044; 600.047; 600.060; 600.075 Approved no  
  Call Number Admin @ si @ BGS2014b Serial 2503  
Permanent link to this record
 

 
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 (down) 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.
 
  Address  
  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  
  Notes MV; 600.096; 600.075 Approved no  
  Call Number Admin @ si @ BTS2017 Serial 2949  
Permanent link to this record
 

 
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 (down) 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.  
  Address  
  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 CARS  
  Notes ADAS; MV; 600.075; 600.085; 600.076; 601.281; 600.118 Approved no  
  Call Number ADAS @ adas @ VBS2017a Serial 2880  
Permanent link to this record
 

 
Author Joan M. Nuñez; Jorge Bernal; F. Javier Sanchez; Fernando Vilariño edit   pdf
doi  openurl
  Title Blood Vessel Characterization in Colonoscopy Images to Improve Polyp Localization Type Conference Article
  Year 2013 Publication Proceedings of the International Conference on Computer Vision Theory and Applications Abbreviated Journal  
  Volume 1 Issue Pages 162-171  
  Keywords (down) Colonoscopy; Blood vessel; Linear features; Valley detection  
  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.
 
  Address Barcelona; February 2013  
  Corporate Author Thesis  
  Publisher SciTePress 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 800 Expedition Conference VISIGRAPP  
  Notes MV; 600.054; 600.057 Approved no  
  Call Number IAM @ iam @ NBS2013 Serial 2198  
Permanent link to this record
 

 
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 (down) 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  
  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  
Permanent link to this record
 

 
Author Jorge Bernal; F. Javier Sanchez; Fernando Vilariño edit   pdf
doi  isbn
openurl 
  Title A Region Segmentation Method for Colonoscopy Images Using a Model of Polyp Appearance Type Conference Article
  Year 2011 Publication 5th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal  
  Volume 6669 Issue Pages 134-143     
  Keywords (down) Colonoscopy, Polyp Detection, Region Merging, Region Segmentation.  
  Abstract This work aims at the segmentation of colonoscopy images into a minimum number of informative regions. Our method performs in a way such, if a polyp is present in the image, it will be exclusively and totally contained in a single region. This result can be used in later stages to classify regions as polyp-containing candidates. The output of the algorithm also defines which regions can be considered as non-informative. The algorithm starts with a high number of initial regions and merges them taking into account the model of polyp appearance obtained from available data. The results show that our segmentations of polyp regions are more accurate than state-of-the-art methods.  
  Address Las Palmas de Gran Canaria, June 2011  
  Corporate Author SpringerLink Thesis  
  Publisher Place of Publication Editor Vitrià, Jordi and Sanches, João and Hernández, Mario  
  Language Summary Language Original Title  
  Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-642-21256-7 Medium  
  Area 800 Expedition Conference IbPRIA  
  Notes MV; Approved no  
  Call Number IAM @ iam @ BSV2011c Serial 1696  
Permanent link to this record
 

 
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 (down) 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  
  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 CARE  
  Notes IAM; MV; 600.075 Approved no  
  Call Number Admin @ si @ GSF2015 Serial 2733  
Permanent link to this record
 

 
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 (down) 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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  Area Expedition Conference  
  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 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 (down) 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 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