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Author Carles Sanchez; Jorge Bernal; Debora Gil; F. Javier Sanchez
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 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 (up) 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
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Author Jorge Bernal
Title Polyp Localization and Segmentation in Colonoscopy Images by Means of a Model of Appearance for Polyps Type Book Whole
Year 2012 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal
Volume Issue Pages
Keywords
Abstract Colorectal cancer is the fourth most common cause of cancer death worldwide and its survival rate depends on the stage in which it is detected on hence the necessity for an early colon screening. There are several screening techniques but colonoscopy is still nowadays the gold standard, although it has some drawbacks such as the miss rate. Our contribution, in the field of intelligent systems for colonoscopy, aims at providing a polyp localization and a polyp segmentation system based on a model of appearance for polyps. To develop both methods we define a model of appearance for polyps, which describes a polyp as enclosed by intensity valleys. The novelty of our contribution resides on the fact that we include in our model aspects of the image formation and we also consider the presence of other elements from the endoluminal scene such as specular highlights and blood vessels, which have an impact on the performance of our methods. In order to develop our polyp localization method we accumulate valley information in order to generate energy maps, which are also used to guide the polyp segmentation. Our methods achieve promising results in polyp localization and segmentation. As we want to explore the usability of our methods we present a comparative analysis between physicians fixations obtained via an eye tracking device and our polyp localization method. The results show that our method is indistinguishable to novice physicians although it is far from expert physicians.
Address
Corporate Author Thesis Ph.D. thesis
Publisher Ediciones Graficas Rey Place of Publication Editor (up) F. Javier Sanchez;Fernando Vilariño
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 Admin @ si @ Ber2012 Serial 2211
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Author Farhan Riaz; Fernando Vilariño; Mario Dinis-Ribeiro; Miguel Coimbraln
Title Identifying Potentially Cancerous Tissues in Chromoendoscopy Images Type Conference Article
Year 2011 Publication 5th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal
Volume 6669 Issue Pages 709-716
Keywords Endoscopy, Computer Assisted Diagnosis, Gradient.
Abstract The dynamics of image acquisition conditions for gastroenterology imaging scenarios pose novel challenges for automatic computer assisted decision systems. Such systems should have the ability to mimic the tissue characterization of the physicians. In this paper, our objective is to compare some feature extraction methods to classify a Chromoendoscopy image into two different classes: Normal and Potentially cancerous. Results show that LoG filters generally give best classification accuracy among the other feature extraction methods considered.
Address Las Palmas de Gran Canaria. Spain
Corporate Author Thesis
Publisher Springer Place of Publication Berlin Editor (up) J. Vitria, J.M. Sanches, and M. Hernandez
Language Summary Language Original Title
Series Editor Series Title 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 Admin @ si @ RVD2011; IAM @ iam @ RVD2011 Serial 1726
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Author Fernando Vilariño; Panagiota Spyridonos; Jordi Vitria; Carolina Malagelada; Petia Radeva
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 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 (up) 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
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Author Jorge Bernal; Fernando Vilariño; F. Javier Sanchez
Title Towards Intelligent Systems for Colonoscopy Type Book Chapter
Year 2011 Publication Colonoscopy Abbreviated Journal
Volume 1 Issue Pages 257-282
Keywords
Abstract In this chapter we present tools that can be used to build intelligent systems for colonoscopy.
The idea is, by using methods based on computer vision and artificial intelligence, add significant value to the colonoscopy procedure. Intelligent systems are being used to assist in other medical interventions
Address
Corporate Author Thesis
Publisher Intech Place of Publication Editor (up) 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
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Author Fernando Vilariño
Title A Machine Learning Approach for Intestinal Motility Assessment with Capsule Endoscopy Type Book Whole
Year 2006 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal
Volume Issue Pages
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 obtained by labelling all the motility events present in a video provided by a capsule with a wireless micro-camera, which is ingested by the patient. However, the visual analysis of these video sequences presents several im- portant drawbacks, mainly related to both the large amount of time needed for the visualization process, and the low prevalence of intestinal contractions in video.
In this work we propose a machine learning system to automatically detect the intestinal contractions in video capsule endoscopy, driving a very useful but not fea- sible clinical routine into a feasible clinical procedure. Our proposal is divided into two different parts: The first part tackles the problem of the automatic detection of phasic contractions in capsule endoscopy videos. Phasic contractions are dynamic events spanning about 4-5 seconds, which show visual patterns with a high variability. Our proposal is based on a sequential design which involves the analysis of textural, color and blob features with powerful classifiers such as SVM. This approach appears to cope with two basic aims: the reduction of the imbalance rate of the data set, and the modular construction of the system, which adds the capability of including domain knowledge as new stages in the cascade. The second part of the current work tackles the problem of the automatic detection of tonic contractions. Tonic contrac- tions manifest in capsule endoscopy as a sustained pattern of the folds and wrinkles of the intestine, which may be prolonged for an undetermined span of time. Our proposal is based on the analysis of the wrinkle patterns, presenting a comparative study of diverse features and classification methods, and providing a set of appro- priate descriptors for their characterization. We provide a detailed analysis of the performance achieved by our system both in a qualitative and a quantitative way.
Address CVC (UAB)
Corporate Author Thesis Ph.D. thesis
Publisher Place of Publication Editor (up) Petia Radeva
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue 84-933652-7-0 Edition
ISSN ISBN Medium
Area 800 Expedition Conference
Notes MV;SIAI Approved no
Call Number Admin @ si @ Vil2006; IAM @ iam @ Vil2006 Serial 738
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Author Panagiota Spyridonos; Fernando Vilariño; Jordi Vitria; Fernando Azpiroz; Petia Radeva
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 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 (up) 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
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Author Carles Sanchez; Debora Gil; Antoni Rosell; Albert Andaluz; F. Javier Sanchez
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 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 (up) 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 Jorge Bernal; F. Javier Sanchez; Fernando Vilariño
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 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 (up) 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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