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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 | 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. | ||||
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Corporate Author | Thesis | Ph.D. thesis | |||
Publisher | Ediciones Graficas Rey | Place of Publication | Editor | 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 | 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 | 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 | 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 |
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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 | 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. |
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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 | 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 |