| Records |
| 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 |
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| Volume |
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Issue |
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Pages |
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| Keywords |
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| 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 |
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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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| Language |
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Summary Language |
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Original Title |
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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 |
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ISBN |
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Medium |
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| Area |
800 |
Expedition |
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Conference |
CASEIB |
| Notes |
MV;SIAI |
Approved |
no |
| Call Number |
Admin @ si @ BSV2010 |
Serial |
1469 |
| Permanent link to this record |
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| 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 |
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| Volume |
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Issue |
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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 |
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Thesis |
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| Publisher |
SciTePress |
Place of Publication |
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Editor |
Djemal, Khalifa |
| Language |
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Summary Language |
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Original Title |
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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 |
MIAD |
| Notes |
MV;SIAI |
Approved |
no |
| Call Number |
IAM @ iam @ BSV2011a |
Serial |
1695 |
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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 |
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| Volume |
6669 |
Issue |
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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 |
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Place of Publication |
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Editor |
Vitrià, Jordi and Sanches, João and Hernández, Mario |
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Summary Language |
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Original Title |
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Series Title |
Lecture Notes in Computer Science |
Abbreviated Series Title |
LNCS |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
978-3-642-21256-7 |
Medium |
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| Area |
800 |
Expedition |
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Conference |
IbPRIA |
| Notes |
MV;SIAI |
Approved |
no |
| Call Number |
IAM @ iam @ BSV2011c |
Serial |
1696 |
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| 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 |
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| Volume |
6668 |
Issue |
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Pages |
76-83 |
| Keywords |
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| 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 |
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Thesis |
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| Publisher |
Springer Link |
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 |
Lecture Notes in Computer Science |
Abbreviated Series Title |
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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 |
ABI |
| Notes |
MV;SIAI |
Approved |
no |
| Call Number |
IAM @ iam @ BSV2011d |
Serial |
1698 |
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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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| Language |
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Summary Language |
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Original Title |
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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 |
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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 |
Jorge Bernal; F. Javier Sanchez; Fernando Vilariño |
| Title |
Impact of Image Preprocessing Methods on Polyp Localization in Colonoscopy Frames |
Type |
Conference Article |
| Year |
2013 |
Publication |
35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
7350 - 7354 |
| Keywords |
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| Abstract |
In this paper we present our image preprocessing methods as a key part of our automatic polyp localization scheme. These methods are used to assess the impact of different endoluminal scene elements when characterizing polyps. More precisely we tackle the influence of specular highlights, blood vessels and black mask surrounding the scene. Experimental results prove that the appropriate handling of these elements leads to a great improvement in polyp localization results. |
| Address |
Osaka; Japan; July 2013 |
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Series Issue |
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Edition |
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| ISSN |
1557-170X |
ISBN |
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Medium |
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| Area |
800 |
Expedition |
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Conference |
EMBC |
| Notes |
MV; 600.047; 600.060;SIAI |
Approved |
no |
| Call Number |
Admin @ si @ BSV2013 |
Serial |
2286 |
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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. |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
Elsevier |
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 |
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 |
