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Author Mirko Arnold; Anarta Ghosh; Gerard Lacey; Stephen Patchett; Hugh Mulcahy edit  openurl
  Title Indistinct frame detection in colonoscopy videos Type Conference Article
  Year 2009 Publication Machine Vision and Image Processing Conference Abbreviated Journal  
  Volume Issue Pages (up) 47-52  
  Keywords  
  Abstract  
  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 800 Expedition Conference  
  Notes MV Approved no  
  Call Number fernando @ fernando @ Serial 2424  
Permanent link to this record
 

 
Author Mirko Arnold; Anarta Ghosh; Glen Doherty; Hugh Mulcahy; Stephen Patchett; Gerard Lacey edit  doi
openurl 
  Title Towards Automatic Direct Observation of Procedure and Skill (DOPS) in Colonoscopy Type Conference Article
  Year 2013 Publication Proceedings of the International Conference on Computer Vision Theory and Applications Abbreviated Journal  
  Volume Issue Pages (up) 48-53  
  Keywords  
  Abstract  
  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 800 Expedition Conference VISIGRAPP  
  Notes MV Approved no  
  Call Number fernando @ fernando @ Serial 2427  
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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 (up) 62-71  
  Keywords 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;SIAI Approved no  
  Call Number IAM @ iam @ BSV2011a Serial 1695  
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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 (up) 71-80  
  Keywords 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;SIAI Approved no  
  Call Number IAM @ iam @ BSV2011b Serial 1699  
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Author Jorge Bernal; F. Javier Sanchez; Fernando Vilariño edit   pdf
url  doi
openurl 
  Title Integration of Valley Orientation Distribution for Polyp Region Identification in Colonoscopy Type Conference Article
  Year 2011 Publication In MICCAI 2011 Workshop on Computational and Clinical Applications in Abdominal Imaging Abbreviated Journal  
  Volume 6668 Issue Pages (up) 76-83  
  Keywords  
  Abstract This work presents a region descriptor based on the integration of the information that the depth of valleys image provides. The depth of valleys image is based on the presence of intensity valleys around polyps due to the image acquisition. Our proposed method consists of defining, for each point, a series of radial sectors around it and then accumulates the maxima of the depth of valleys image only if the orientation of the intensity valley coincides with the orientation of the sector above. We apply our descriptor to a prior segmentation of the images and we present promising results on polyp detection, outperforming other approaches that also integrate depth of valleys information.  
  Address Toronto, Canada  
  Corporate Author Thesis  
  Publisher Springer Link Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area 800 Expedition Conference ABI  
  Notes MV;SIAI Approved no  
  Call Number IAM @ iam @ BSV2011d Serial 1698  
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 (up) 134-143     
  Keywords 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;SIAI Approved no  
  Call Number IAM @ iam @ BSV2011c Serial 1696  
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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 (up) 153--161  
  Keywords 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  
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Author Panagiota Spyridonos; Fernando Vilariño; Jordi Vitria; Fernando Azpiroz; Petia Radeva edit   pdf
doi  openurl
  Title Anisotropic Feature Extraction from Endoluminal Images for Detection of Intestinal Contractions Type Book Chapter
  Year 2006 Publication 9th International Conference on Medical Image Computing and Computer–Assisted Intervention Abbreviated Journal  
  Volume 4191 Issue Pages (up) 161–168  
  Keywords  
  Abstract Wireless endoscopy is a very recent and at the same time unique technique allowing to visualize and study the occurrence of con- tractions and to analyze the intestine motility. Feature extraction is es- sential for getting efficient patterns to detect contractions in wireless video endoscopy of small intestine. We propose a novel method based on anisotropic image filtering and efficient statistical classification of con- traction features. In particular, we apply the image gradient tensor for mining informative skeletons from the original image and a sequence of descriptors for capturing the characteristic pattern of contractions. Fea- tures extracted from the endoluminal images were evaluated in terms of their discriminatory ability in correct classifying images as either belong- ing to contractions or not. Classification was performed by means of a support vector machine classifier with a radial basis function kernel. Our classification rates gave sensitivity of the order of 90.84% and specificity of the order of 94.43% respectively. These preliminary results highlight the high efficiency of the selected descriptors and support the feasibility of the proposed method in assisting the automatic detection and analysis of contractions.  
  Address Copenhagen (Denmark)  
  Corporate Author Thesis  
  Publisher Springer Verlag Place of Publication Berlin Heidelberg Editor R. Larsen, M. Nielsen, and J. Sporring  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area 800 Expedition Conference MICCAI06  
  Notes MV;OR;MILAB;SIAI Approved no  
  Call Number BCNPCL @ bcnpcl @ SVV2006; IAM @ iam @ SVV2006 Serial 725  
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 (up) 162-171  
  Keywords 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;SIAI Approved no  
  Call Number IAM @ iam @ NBS2013 Serial 2198  
Permanent link to this record
 

 
Author Fernando Vilariño; Panagiota Spyridonos; Jordi Vitria; Carolina Malagelada; Petia Radeva edit   pdf
doi  openurl
  Title Linear Radial Patterns Characterization for Automatic Detection of Tonic Intestinal Contractions Type Book Chapter
  Year 2006 Publication 11th Iberoamerican Congress on Pattern Recognition Abbreviated Journal  
  Volume 4225 Issue Pages (up) 178–187  
  Keywords  
  Abstract This work tackles the categorization of general linear radial patterns by means of the valleys and ridges detection and the use of descriptors of directional information, which are provided by steerable filters in different regions of the image. We successfully apply our proposal in the specific case of automatic detection of tonic contractions in video capsule endoscopy, which represent a paradigmatic example of linear radial patterns.  
  Address Cancun (Mexico)  
  Corporate Author Thesis  
  Publisher Springer Verlag Place of Publication Berlin Heidelberg Editor .F. Mart ́ınez-Trinidad et al  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area 800 Expedition Conference  
  Notes MV;OR;MILAB;SIAI Approved no  
  Call Number BCNPCL @ bcnpcl @ VSV2006c; IAM @ iam @ VSB2006f Serial 728  
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Author Fernando Vilariño; Panagiota Spyridonos; Jordi Vitria; Carolina Malagelada; Petia Radeva edit   pdf
doi  openurl
  Title A Machine Learning framework using SOMs: Applications in the Intestinal Motility Assessment Type Book Chapter
  Year 2006 Publication 11th Iberoamerican Congress on Pattern Recognition Abbreviated Journal  
  Volume 4225 Issue Pages (up) 188–197  
  Keywords  
  Abstract Small Bowel Motility Assessment by means of Wireless Capsule Video Endoscopy constitutes a novel clinical methodology in which a capsule with a micro-camera attached to it is swallowed by the patient, emitting a RF signal which is recorded as a video of its trip throughout the gut. In order to overcome the main drawbacks associated with this technique -mainly related to the large amount of visualization time required-, our efforts have been focused on the development of a machine learning system, built up in sequential stages, which provides the specialists with the useful part of the video, rejecting those parts not valid for analysis. We successfully used Self Organized Maps in a general semi-supervised framework with the aim of tackling the different learning stages of our system. The analysis of the diverse types of images and the automatic detection of intestinal contractions is performed under the perspective of intestinal motility assessment in a clinical environment.  
  Address Cancun (Mexico)  
  Corporate Author Thesis  
  Publisher Springer Verlag Place of Publication Berlin-Heidelberg Editor J.P. Martinez–Trinidad et al  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area 800 Expedition Conference CIARP06  
  Notes MV;OR;MILAB;SIAI Approved no  
  Call Number BCNPCL @ bcnpcl @ VSV2006d; IAM @ iam @ VSV2006e Serial 729  
Permanent link to this record
 

 
Author Fernando Vilariño; Panagiota Spyridonos; Fosca De Iorio; Jordi Vitria; Fernando Azpiroz; Petia Radeva edit   pdf
doi  openurl
  Title Intestinal Motility Assessment With Video Capsule Endoscopy: Automatic Annotation of Phasic Intestinal Contractions Type Journal Article
  Year 2010 Publication IEEE Transactions on Medical Imaging Abbreviated Journal TMI  
  Volume 29 Issue 2 Pages (up) 246-259  
  Keywords  
  Abstract Intestinal motility assessment with video capsule endoscopy arises as a novel and challenging clinical fieldwork. This technique is based on the analysis of the patterns of intestinal contractions shown in a video provided by an ingestible capsule with a wireless micro-camera. The manual labeling of all the motility events requires large amount of time for offline screening in search of findings with low prevalence, which turns this procedure currently unpractical. In this paper, we propose a machine learning system to automatically detect the phasic intestinal contractions in video capsule endoscopy, driving a useful but not feasible clinical routine into a feasible clinical procedure. Our proposal is based on a sequential design which involves the analysis of textural, color, and blob features together with SVM classifiers. Our approach tackles the reduction of the imbalance rate of data and allows the inclusion of domain knowledge as new stages in the cascade. We present a detailed analysis, both in a quantitative and a qualitative way, by providing several measures of performance and the assessment study of interobserver variability. Our system performs at 70% of sensitivity for individual detection, whilst obtaining equivalent patterns to those of the experts for density of contractions.  
  Address  
  Corporate Author IEEE Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0278-0062 ISBN Medium  
  Area 800 Expedition Conference  
  Notes MILAB;MV;OR;SIAI Approved no  
  Call Number BCNPCL @ bcnpcl @ VSD2010; IAM @ iam @ VSI2010 Serial 1281  
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Author Santiago Segui; Laura Igual; Fernando Vilariño; Petia Radeva; Carolina Malagelada; Fernando Azpiroz; Jordi Vitria edit   pdf
url  isbn
openurl 
  Title Diagnostic System for Intestinal Motility Disfunctions Using Video Capsule Endoscopy Type Book Chapter
  Year 2008 Publication Computer Vision Systems. 6th International Abbreviated Journal  
  Volume 5008 Issue Pages (up) 251–260  
  Keywords  
  Abstract Wireless Video Capsule Endoscopy is a clinical technique consisting of the analysis of images from the intestine which are pro- vided by an ingestible device with a camera attached to it. In this paper we propose an automatic system to diagnose severe intestinal motility disfunctions using the video endoscopy data. The system is based on the application of computer vision techniques within a machine learn- ing framework in order to obtain the characterization of diverse motil- ity events from video sequences. We present experimental results that demonstrate the effectiveness of the proposed system and compare them with the ground-truth provided by the gastroenterologists.  
  Address Santorini (Greece)  
  Corporate Author Thesis  
  Publisher Springer-Verlag Place of Publication Berlin Heidelberg Editor A. Gasteratos, M. Vincze, and J.K. Tsotsos  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-540-79546-9 Medium  
  Area 800 Expedition Conference ICVS  
  Notes OR; MV; MILAB; SIAI Approved no  
  Call Number BCNPCL @ bcnpcl @ SIV2008; IAM @ iam @ SIV2008 Serial 962  
Permanent link to this record
 

 
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 (up) 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  
  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;SIAI Approved no  
  Call Number IAM @ iam @ BVS2011 Serial 1697  
Permanent link to this record
 

 
Author Joan M. Nuñez; Debora Gil; Fernando Vilariño edit  doi
openurl 
  Title Finger joint characterization from X-ray images for rheymatoid arthritis assessment Type Conference Article
  Year 2013 Publication 6th International Conference on Biomedical Electronics and Devices Abbreviated Journal  
  Volume Issue Pages (up) 288-292  
  Keywords Rheumatoid Arthritis; X-Ray; Hand Joint; Sclerosis; Sharp Van der Heijde  
  Abstract In this study we propose amodular systemfor automatic rheumatoid arthritis assessment which provides a joint space width measure. A hand joint model is proposed based on the accurate analysis of a X-ray finger joint image sample set. This model shows that the sclerosis and the lower bone are the main necessary features in order to perform a proper finger joint characterization. We propose sclerosis and lower bone detection methods as well as the experimental setup necessary for its performance assessment. Our characterization is used to propose and compute a joint space width score which is shown to be related to the different degrees of arthritis. This assertion is verified by comparing our proposed score with Sharp Van der Heijde score, confirming that the lower our score is the more advanced is the patient affection.  
  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 BIODEVICES  
  Notes IAM;MV; 600.057; 600.054;SIAI Approved no  
  Call Number IAM @ iam @ NGV2013 Serial 2196  
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