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Author |
Mirko Arnold; Stephan Ameling; Anarta Ghosh; Gerard Lacey |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Quality Improvement of Endoscopy Videos |
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Conference Article |
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2011 |
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Proceedings of the 8th IASTED International Conference on Biomedical Engineering |
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723 |
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Call Number |
fernando @ fernando @ |
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2426 |
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Author |
Mirko Arnold; Anarta Ghosh; Glen Doherty; Hugh Mulcahy; Stephen Patchett; Gerard Lacey |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Towards Automatic Direct Observation of Procedure and Skill (DOPS) in Colonoscopy |
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Conference Article |
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2013 |
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Proceedings of the International Conference on Computer Vision Theory and Applications |
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48-53 |
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800 |
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VISIGRAPP |
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MV |
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fernando @ fernando @ |
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2427 |
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Author |
Stefan Ameling; Stephan Wirth; Dietrich Paulus; Gerard Lacey; Fernando Vilariño |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Texture-based Polyp Detection in Colonoscopy |
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Conference Article |
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Year |
2009 |
Publication |
Proc. BILDVERARBEITUNG FÜR DIE MEDIZIN |
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MV;SIAI |
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fernando @ fernando @ |
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2428 |
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Author |
Fernando Vilariño; Gerard Lacey |
![find record details (via OpenURL) openurl](img/xref.gif)
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Title |
QUALITY ASSESSMENT IN COLONOSCOPY New challenges through computer vision-based systems |
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Conference Article |
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Year |
2009 |
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in Proc. 3rd International Conference on Biomedical Electronics and Devices |
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MV;SIAI |
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fernando @ fernando @ |
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2430 |
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Author |
Fernando Vilariño; Gerard Lacey; Jiang Zhou; Hugh Mulcahy; Stephen Patchett |
![find record details (via OpenURL) openurl](img/xref.gif)
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Title |
Automatic Labeling of Colonoscopy Video for Cancer Detection |
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Conference Article |
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Year |
2007 |
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In Proc. berian Conference, IbPRIA |
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290-297 |
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MV;SIAI |
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fernando @ fernando @ |
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2431 |
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Author |
Jorge Bernal |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Use of Projection and Back-projection Methods in Bidimensional Computed Tomography Image Reconstruction |
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Report |
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Year |
2009 |
Publication |
CVC Tecnical Report |
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141 |
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Projection, Back-projection, CT scan, Euclidean geometry, Radon transform |
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Abstract |
One of the biggest drawbacks related to the use of CT scanners is the cost (in memory and in time) associated. In this project many methods to simulate their functioning, but in a more feasible way (taking an industrial point of view), will be studied.
The main group of techniques that are being used are the one entitled as ’back-projection’. The concept behind is to simulate the X ray emission in CT scans by lines that cross with the image we want to reconstruct.
In the first part of this document euclidean geometry is used to face the tasks of projec- tion and back-projection. After analysing the results achieved it has been proved that this approach does not lead to a fully perfect reconstruction (and also has some other problems related to running time and memory cost). Because of this in the second part of the document ’Filtered Back-projection’ method is introduced in order to improve the results.
Filtered Back-projection methods rely on mathematical transforms (Fourier, Radon) in order to provide more accurate results that can be obtained in much less time. The main cause of this better results is the use of a filtering process before the back-projection in order to avoid high frequency-caused errors.
As a result of this project two different implementations (one for each approach) had been implemented in order to compare their performance. |
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Corporate Author ![sorted by Corporate Author field, ascending order (up)](img/sort_asc.gif) |
Computer Vision Center |
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Master's thesis |
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Barcelona, Spain |
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MV; |
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IAM @ iam @ Ber2009 |
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1693 |
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Author |
Fernando Vilariño; Panagiota Spyridonos; Fosca De Iorio; Jordi Vitria; Fernando Azpiroz; Petia Radeva |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Intestinal Motility Assessment With Video Capsule Endoscopy: Automatic Annotation of Phasic Intestinal Contractions |
Type |
Journal Article |
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Year |
2010 |
Publication |
IEEE Transactions on Medical Imaging |
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TMI |
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Volume |
29 |
Issue |
2 |
Pages |
246-259 |
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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. |
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IEEE |
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0278-0062 |
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800 |
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MILAB;MV;OR;SIAI |
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BCNPCL @ bcnpcl @ VSD2010; IAM @ iam @ VSI2010 |
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1281 |
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Permanent link to this record |
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Author |
Jorge Bernal; F. Javier Sanchez; Fernando Vilariño |
![download PDF file pdf](img/file_PDF.gif)
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Title |
A Region Segmentation Method for Colonoscopy Images Using a Model of Polyp Appearance |
Type |
Conference Article |
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Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
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6669 |
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134-143 |
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Colonoscopy, Polyp Detection, Region Merging, Region Segmentation. |
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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. |
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Las Palmas de Gran Canaria, June 2011 |
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Corporate Author ![sorted by Corporate Author field, ascending order (up)](img/sort_asc.gif) |
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Vitrià, Jordi and Sanches, João and Hernández, Mario |
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Lecture Notes in Computer Science |
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978-3-642-21256-7 |
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IbPRIA |
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MV;SIAI |
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IAM @ iam @ BSV2011c |
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1696 |
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Permanent link to this record |
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Author |
Gerard Lacey; Fernando Vilariño |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Endoscopy system with motion sensors |
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Patent |
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Year |
2011 |
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US 2011/0032347 A1 |
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An endoscopy system (1) comprises an endoscope (2) with a camera (3) at its tip. The endoscope extends through an endoscope guide (4) for guiding movement of the endoscope and for measurement of its movement as it enters the body. The guide (4) comprises a generally conical body (5) having a through passage (105) through which the endoscope (2) extends. A motion sensor comprises an optical transmitter (7) and a detector (8) mounted alongside the passage (105) to measure the insertion-withdrawal linear motion and also rotation of the endoscope by the endoscopist's hand. The system (1) also comprises a flexure controller (10) having wheels operated by the endoscopist. The camera (3), the motion sensor (7/8), and the flexure controller (10) are all connected to a processor (11) which feeds a display. |
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Jacobson Holman PPLC; 400 Seventh Street, N.W. Suite 600; Whashington DC 20004 DC |
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USPTO |
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IAM @ iam @ LaV2011 |
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1703 |
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