Home | << 1 2 3 >> |
Records | |||||
---|---|---|---|---|---|
Author | Joan M. Nuñez; Jorge Bernal; F. Javier Sanchez; Fernando Vilariño | ||||
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 | 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 | 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 | 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 | 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 | 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 | 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 | 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 | ||
Permanent link to this record | |||||
Author | Jorge Bernal; F. Javier Sanchez; Fernando Vilariño | ||||
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 | 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 | ||||
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 | 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 | ||
Permanent link to this record | |||||
Author | Jorge Bernal; F. Javier Sanchez; Fernando Vilariño | ||||
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 | 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 | ||
Permanent link to this record | |||||
Author | Mirko Arnold; Anarta Ghosh; Glen Doherty; Hugh Mulcahy; Stephen Patchett; Gerard Lacey | ||||
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 | 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 | ||
Permanent link to this record | |||||
Author | Mirko Arnold; Anarta Ghosh; Gerard Lacey; Stephen Patchett; Hugh Mulcahy | ||||
Title | Indistinct frame detection in colonoscopy videos | Type | Conference Article | ||
Year | 2009 | Publication | Machine Vision and Image Processing Conference | Abbreviated Journal | |
Volume | Issue | Pages | 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 | 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 | 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 | Fernando Vilariño; Panagiota Spyridonos; Jordi Vitria; Fernando Azpiroz; Petia Radeva | ||||
Title | Cascade analysis for intestinal contraction detection | Type | Conference Article | ||
Year | 2006 | Publication | 20th International Congress and exhibition Computer Assisted Radiology and Surgery | Abbreviated Journal | |
Volume | Issue | Pages | 9-10 | ||
Keywords | intestine video analysis, anisotropic features, support vector machine, cascade of classifiers | ||||
Abstract | In this work, we address the study of intestinal contractions in a novel approach based on a machine learning framework to process data from Wireless Capsule Video Endoscopy. Wireless endoscopy represents a unique way to visualize the intestine motility by creating long videos to visualize intestine dynamics. In this paper we argue that to analyze huge amount of wireless endoscopy data and define robust methods for contraction detection we should base our approach on sophisticated machine learning techniques. In particular, we propose a cascade of classifiers in order to remove different physiological phenomenon and obtain the motility pattern of small intestines. Our results show obtaining high specificity and sensitivity rates that highlight the high efficiency of the selected approach and support the feasibility of the proposed methodology in the automatic detection and analysis of intestine contractions. | ||||
Address | Osaka (Japan) | ||||
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 | CARS | |
Notes | MV;OR;MILAB;SIAI | Approved | no | ||
Call Number | BCNPCL @ bcnpcl @ VSV2006a; IAM @ iam @ VSV2006h | Serial | 726 | ||
Permanent link to this record | |||||
Author | Rozenn Dhayot; Fernando Vilariño; Gerard Lacey | ||||
Title | Improving the Quality of Color Colonoscopy Videos | Type | Journal Article | ||
Year | 2008 | Publication | EURASIP Journal on Image and Video Processing | Abbreviated Journal | EURASIP JIVP |
Volume | 139429 | Issue | 1 | Pages | 1-9 |
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;SIAI | Approved | no | ||
Call Number | fernando @ fernando @ | Serial | 2422 | ||
Permanent link to this record | |||||
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 | 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 | ||
Permanent link to this record | |||||
Author | Jorge Bernal; Fernando Vilariño; F. Javier Sanchez | ||||
Title | Feature Detectors and Feature Descriptors: Where We Are Now | Type | Report | ||
Year | 2010 | Publication | CVC Technical Report | Abbreviated Journal | |
Volume | 154 | Issue | Pages | ||
Keywords | |||||
Abstract | Feature Detection and Feature Description are clearly nowadays topics. Many Computer Vision applications rely on the use of several of these techniques in order to extract the most significant aspects of an image so they can help in some tasks such as image retrieval, image registration, object recognition, object categorization and texture classification, among others. In this paper we define what Feature Detection and Description are and then we present an extensive collection of several methods in order to show the different techniques that are being used right now. The aim of this report is to provide a glimpse of what is being used currently in these fields and to serve as a starting point for future endeavours. | ||||
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;SIAI | Approved | no | ||
Call Number | Admin @ si @ BVS2010; IAM @ iam @ BVS2010 | Serial | 1348 | ||
Permanent link to this record | |||||
Author | Jorge Bernal; F. Javier Sanchez; Fernando Vilariño | ||||
Title | Reduction of Pattern Search Area in Colonoscopy Images by Merging Non-Informative Regions | Type | Conference Article | ||
Year | 2010 | Publication | 28th Congreso Anual de la Sociedad Española de Ingeniería Biomédica | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | |||||
Abstract | One of the first usual steps in pattern recognition schemas is image segmentation, in order to reduce the dimensionality of the problem and manage smaller quantity of data. In our case as we are pursuing real-time colon cancer polyp detection, this step is crucial. In this paper we present a non-informative region estimation algorithm that will let us discard some parts of the image where we will not expect to find colon cancer polyps. The performance of our approach will be measured in terms of both non-informative areas elimination and polyps’ areas preserving. The results obtained show the importance of having correct non- informative region estimation in order to fasten the whole recognition process. | ||||
Address | Madrid (Spain) | ||||
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 | CASEIB | |
Notes | MV;SIAI | Approved | no | ||
Call Number | Admin @ si @ BSV2010 | Serial | 1469 | ||
Permanent link to this record |