| Records |
| Author |
Fernando Vilariño; Gerard Lacey; Jiang Zhou; Hugh Mulcahy; Stephen Patchett |
| Title |
Automatic Labeling of Colonoscopy Video for Cancer Detection |
Type |
Conference Article |
| Year |
2007 |
Publication |
In Proc. berian Conference, IbPRIA |
Abbreviated Journal |
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| Volume |
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Issue  |
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Pages |
290-297 |
| Keywords |
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| Abstract |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
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Medium |
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| Area |
800 |
Expedition |
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Conference |
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| Notes |
MV;SIAI |
Approved |
no |
| Call Number |
fernando @ fernando @ |
Serial |
2431 |
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| 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 |
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| 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 |
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Thesis |
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| Publisher |
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Place of Publication |
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Editor |
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Summary Language |
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Original Title |
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Series Title |
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Edition |
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| ISSN |
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ISBN |
978-1-60750-841-0 |
Medium |
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| Area |
800 |
Expedition |
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Conference |
CCIA |
| Notes |
MV;SIAI |
Approved |
no |
| Call Number |
IAM @ iam @ BSV2011b |
Serial |
1699 |
| Permanent link to this record |
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| 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 |
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| Abstract |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
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Medium |
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| Area |
800 |
Expedition |
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Conference |
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| Notes |
MV;SIAI |
Approved |
no |
| Call Number |
fernando @ fernando @ |
Serial |
2422 |
| Permanent link to this record |
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| Author |
Fernando Vilariño; Panagiota Spyridonos; Fosca De Iorio; Jordi Vitria; Fernando Azpiroz; Petia Radeva |
| 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 |
246-259 |
| Keywords |
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| 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 |
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| Corporate Author |
IEEE |
Thesis |
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Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0278-0062 |
ISBN |
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Medium |
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| Area |
800 |
Expedition |
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Conference |
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| Notes |
MILAB;MV;OR;SIAI |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ VSD2010; IAM @ iam @ VSI2010 |
Serial |
1281 |
| Permanent link to this record |
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| Author |
Fernando Vilariño; Stephan Ameling; Gerard Lacey; Stephen Patchett; Hugh Mulcahy |
| Title |
Eye Tracking Search Patterns in Expert and Trainee Colonoscopists: A Novel Method of Assessing Endoscopic Competency? |
Type |
Journal Article |
| Year |
2009 |
Publication |
Gastrointestinal Endoscopy |
Abbreviated Journal |
GI |
| Volume |
69 |
Issue |
5 |
Pages |
370 |
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Edition |
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ISBN |
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Medium |
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| Area |
800 |
Expedition |
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Conference |
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| Notes |
MV;SIAI |
Approved |
no |
| Call Number |
fernando @ fernando @ |
Serial |
2420 |
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| Author |
Santiago Segui; Michal Drozdzal; Fernando Vilariño; Carolina Malagelada; Fernando Azpiroz; Petia Radeva; Jordi Vitria |
| Title |
Categorization and Segmentation of Intestinal Content Frames for Wireless Capsule Endoscopy |
Type |
Journal Article |
| Year |
2012 |
Publication |
IEEE Transactions on Information Technology in Biomedicine |
Abbreviated Journal |
TITB |
| Volume |
16 |
Issue |
6 |
Pages |
1341-1352 |
| Keywords |
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| Abstract |
Wireless capsule endoscopy (WCE) is a device that allows the direct visualization of gastrointestinal tract with minimal discomfort for the patient, but at the price of a large amount of time for screening. In order to reduce this time, several works have proposed to automatically remove all the frames showing intestinal content. These methods label frames as {intestinal content – clear} without discriminating between types of content (with different physiological meaning) or the portion of image covered. In addition, since the presence of intestinal content has been identified as an indicator of intestinal motility, its accurate quantification can show a potential clinical relevance. In this paper, we present a method for the robust detection and segmentation of intestinal content in WCE images, together with its further discrimination between turbid liquid and bubbles. Our proposal is based on a twofold system. First, frames presenting intestinal content are detected by a support vector machine classifier using color and textural information. Second, intestinal content frames are segmented into {turbid, bubbles, and clear} regions. We show a detailed validation using a large dataset. Our system outperforms previous methods and, for the first time, discriminates between turbid from bubbles media. |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
1089-7771 |
ISBN |
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Medium |
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| Area |
800 |
Expedition |
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Conference |
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| Notes |
MILAB; MV; OR;SIAI |
Approved |
no |
| Call Number |
Admin @ si @ SDV2012 |
Serial |
2124 |
| Permanent link to this record |
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| Author |
Fernando Vilariño; Ludmila I. Kuncheva; Petia Radeva |
| Title |
ROC curves and video analysis optimization in intestinal capsule endoscopy |
Type |
Journal Article |
| Year |
2006 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
| Volume |
27 |
Issue |
8 |
Pages |
875–881 |
| Keywords |
ROC curves; Classification; Classifiers ensemble; Detection of intestinal contractions; Imbalanced classes; Wireless capsule endoscopy |
| Abstract |
Wireless capsule endoscopy involves inspection of hours of video material by a highly qualified professional. Time episodes corresponding to intestinal contractions, which are of interest to the physician constitute about 1% of the video. The problem is to label automatically time episodes containing contractions so that only a fraction of the video needs inspection. As the classes of contraction and non-contraction images in the video are largely imbalanced, ROC curves are used to optimize the trade-off between false positive and false negative rates. Classifier ensemble methods and simple classifiers were examined. Our results reinforce the claims from recent literature that classifier ensemble methods specifically designed for imbalanced problems have substantial advantages over simple classifiers and standard classifier ensembles. By using ROC curves with the bagging ensemble method the inspection time can be drastically reduced at the expense of a small fraction of missed contractions. |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
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Medium |
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| Area |
800 |
Expedition |
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Conference |
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| Notes |
MILAB;MV;SIAI |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ VKR2006; IAM @ iam @ VKR2006 |
Serial |
647 |
| Permanent link to this record |
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| Author |
Jorge Bernal; F. Javier Sanchez; Fernando Vilariño |
| Title |
Towards Automatic Polyp Detection with a Polyp Appearance Model |
Type |
Journal Article |
| Year |
2012 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
| Volume |
45 |
Issue |
9 |
Pages |
3166-3182 |
| Keywords |
Colonoscopy,PolypDetection,RegionSegmentation,SA-DOVA descriptot |
| Abstract |
This work aims at the automatic polyp detection by using a model of polyp appearance in the context of the analysis of colonoscopy videos. Our method consists of three stages: region segmentation, region description and region classification. The performance of our region segmentation method guarantees that if a polyp is present in the image, it will be exclusively and totally contained in a single region. The output of the algorithm also defines which regions can be considered as non-informative. We define as our region descriptor the novel Sector Accumulation-Depth of Valleys Accumulation (SA-DOVA), which provides a necessary but not sufficient condition for the polyp presence. Finally, we classify our segmented regions according to the maximal values of the SA-DOVA descriptor. Our preliminary classification results are promising, especially when classifying those parts of the image that do not contain a polyp inside. |
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| Publisher |
Elsevier |
Place of Publication |
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Series Title |
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Series Issue |
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Edition |
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| ISSN |
0031-3203 |
ISBN |
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Medium |
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| Area |
800 |
Expedition |
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Conference |
IbPRIA |
| Notes |
MV;SIAI |
Approved |
no |
| Call Number |
Admin @ si @ BSV2012; IAM @ iam |
Serial |
1997 |
| Permanent link to this record |
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| Author |
Mirko Arnold; Anarta Ghosh; Stephen Ameling; G Lacey |
| Title |
Automatic segmentation and inpainting of specular highlights for endoscopic imaging |
Type |
Journal Article |
| Year |
2010 |
Publication |
EURASIP Journal on Image and Video Processing |
Abbreviated Journal |
EURASIP JIVP |
| Volume |
2010 |
Issue |
9 |
Pages |
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| Area |
800 |
Expedition |
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Conference |
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| Notes |
MV |
Approved |
no |
| Call Number |
fernando @ fernando @ |
Serial |
2423 |
| Permanent link to this record |
