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Author |
Fernando Vilariño; Panagiota Spyridonos; Jordi Vitria; Fernando Azpiroz; Petia Radeva |
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Title |
Automatic Detection of Intestinal Juices in Wireless Capsule Video Endoscopy |
Type |
Conference Article |
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Year |
2006 |
Publication |
18th International Conference on Pattern Recognition |
Abbreviated Journal |
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Volume |
4 |
Issue |
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Pages |
719-722 |
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Keywords |
Clinical diagnosis , Endoscopes , Fluids and secretions , Gabor filters , Hospitals , Image sequence analysis , Intestines , Lighting , Shape , Visualization |
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Abstract |
Wireless capsule video endoscopy is a novel and challenging clinical technique, whose major reported drawback relates to the high amount of time needed for video visualization. In this paper, we propose a method for the rejection of the parts of the video resulting not valid for analysis by means of automatic detection of intestinal juices. We applied Gabor filters for the characterization of the bubble-like shape of intestinal juices in fasting patients. Our method achieves a significant reduction in visualization time, with no relevant loss of valid frames. The proposed approach is easily extensible to other image analysis scenarios where the described pattern of bubbles can be found. |
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Hong Kong |
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ISSN |
1051-4651 |
ISBN |
0-7695-2521-0 |
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800 |
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ICPR |
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MV;OR;MILAB;SIAI |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ VSV2006b; IAM @ iam @ VSV2006g |
Serial |
727 |
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Permanent link to this record |
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Author |
Fernando Vilariño; Panagiota Spyridonos; Jordi Vitria; C. Malagelada; Petia Radeva |
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Title |
Linear Radial Patterns Characterization for Automatic Detection of Tonic Intestinal Contractions |
Type |
Book Chapter |
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Year |
2006 |
Publication |
11th Iberoamerican Congress on Pattern Recognition |
Abbreviated Journal |
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Volume |
4225 |
Issue |
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Pages |
178–187 |
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Abstract |
This work tackles the categorization of general linear radial patterns by means of the valleys and ridges detection and the use of descriptors of directional information, which are provided by steerable filters in different regions of the image. We successfully apply our proposal in the specific case of automatic detection of tonic contractions in video capsule endoscopy, which represent a paradigmatic example of linear radial patterns. |
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Address |
Cancun (Mexico) |
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Publisher |
Springer Verlag |
Place of Publication |
Berlin Heidelberg |
Editor |
.F. Mart ́ınez-Trinidad et al |
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LNCS |
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800 |
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MV;OR;MILAB;SIAI |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ VSV2006c; IAM @ iam @ VSB2006f |
Serial |
728 |
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Permanent link to this record |
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Author |
Fernando Vilariño; Panagiota Spyridonos; Jordi Vitria; C. Malagelada; Petia Radeva |
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Title |
A Machine Learning framework using SOMs: Applications in the Intestinal Motility Assessment |
Type |
Book Chapter |
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Year |
2006 |
Publication |
11th Iberoamerican Congress on Pattern Recognition |
Abbreviated Journal |
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Volume |
4225 |
Issue |
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Pages |
188–197 |
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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. |
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Cancun (Mexico) |
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Springer Verlag |
Place of Publication |
Berlin-Heidelberg |
Editor |
J.P. Martinez–Trinidad et al |
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LNCS |
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Area |
800 |
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Conference |
CIARP06 |
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Notes ![sorted by Notes field, ascending order (up)](img/sort_asc.gif) |
MV;OR;MILAB;SIAI |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ VSV2006d; IAM @ iam @ VSV2006e |
Serial |
729 |
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Permanent link to this record |
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Author |
Panagiota Spyridonos; Fernando Vilariño; Jordi Vitria; Petia Radeva; Fernando Azpiroz; Juan Malagelada |
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Title |
Device, system and method for automatic detection of contractile activity in an image frame |
Type |
Patent |
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Year |
2011 |
Publication |
US 2011/0044515 A1 |
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A device, system and method for automatic detection of contractile activity of a body lumen in an image frame is provided, wherein image frames during contractile activity are captured and/or image frames including contractile activity are automatically detected, such as through pattern recognition and/or feature extraction to trace image frames including contractions, e.g., with wrinkle patterns. A manual procedure of annotation of contractions, e.g. tonic contractions in capsule endoscopy, may consist of the visualization of the whole video by a specialist, and the labeling of the contraction frames. Embodiments of the present invention may be suitable for implementation in an in vivo imaging system. |
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Address |
Pearl Cohen Zedek Latzer, LLP, 1500 Broadway 12th Floor, New York (NY) 10036 (US) |
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US Patent Office |
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Notes ![sorted by Notes field, ascending order (up)](img/sort_asc.gif) |
MV;OR;MILAB;SIAI |
Approved |
no |
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Call Number |
IAM @ iam @ SVV2011 |
Serial |
1701 |
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Permanent link to this record |
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Author |
Fernando Vilariño; Panagiota Spyridonos; Petia Radeva; Jordi Vitria; Fernando Azpiroz; Juan Malagelada |
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Title |
Method for automatic classification of in vivo images |
Type |
Patent |
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Year |
2010 |
Publication |
US 2010/0046816 |
Abbreviated Journal |
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Abstract |
A method for automatically detecting a post-duodenal boundary in an image stream of the gastrointestinal (GI) tract. The image stream is sampled to obtain a reduced set of images for processing. The reduced set of images is filtered to remove non-valid frames or non-valid portions of frames, thereby generating a filtered set of valid images. A polar representation of the valid images is generated. Textural features of the polar representation are processed to detect the post-duodenal boundary of the GI tract. |
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800 |
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Notes ![sorted by Notes field, ascending order (up)](img/sort_asc.gif) |
MV;OR;MILAB;SIAI |
Approved |
no |
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Call Number |
IAM @ iam @ VSR2010 |
Serial |
1702 |
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Permanent link to this record |
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Author |
Fernando Vilariño; Panagiota Spyridonos; Petia Radeva; Jordi Vitria; Fernando Azpiroz; Juan Malagelada |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Device, system and method for measurement and analysis of contractile activity |
Type |
Patent |
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Year |
2009 |
Publication |
US 2009/0202117 A1 |
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Abstract |
A method and system for determining intestinal dysfunction condition are provided by classifying and analyzing image frames captured in-vivo. The method and system also relate to the detection of contractile activity in intestinal tracts, to automatic detection of video image frames taken in the gastrointestinal tract including contractile activity, and more particularly to measurement and analysis of contractile activity of the GI tract based on image intensity of in vivo image data. |
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Address |
Pearl Cohen Zedek Latzer |
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800 |
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Notes ![sorted by Notes field, ascending order (up)](img/sort_asc.gif) |
MV;OR;MILAB;SIAI |
Approved |
no |
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Call Number |
IAM @ iam @ VSR2009 |
Serial |
1704 |
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Permanent link to this record |
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Author |
Fernando Vilariño |
![download PDF file pdf](img/file_PDF.gif)
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Title |
A Machine Learning Approach for Intestinal Motility Assessment with Capsule Endoscopy |
Type |
Book Whole |
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Year |
2006 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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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 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) |
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Thesis |
Ph.D. thesis |
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Place of Publication |
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Editor |
Petia Radeva |
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84-933652-7-0 |
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800 |
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MV;SIAI |
Approved |
no |
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Call Number |
Admin @ si @ Vil2006; IAM @ iam @ Vil2006 |
Serial |
738 |
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Permanent link to this record |
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Author |
Jorge Bernal; Fernando Vilariño; F. Javier Sanchez |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Feature Detectors and Feature Descriptors: Where We Are Now |
Type |
Report |
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Year |
2010 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
154 |
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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. |
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800 |
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MV;SIAI |
Approved |
no |
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Call Number |
Admin @ si @ BVS2010; IAM @ iam @ BVS2010 |
Serial |
1348 |
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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 |
Reduction of Pattern Search Area in Colonoscopy Images by Merging Non-Informative Regions |
Type |
Conference Article |
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Year |
2010 |
Publication |
28th Congreso Anual de la Sociedad Española de Ingeniería Biomédica |
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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. |
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Madrid (Spain) |
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800 |
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CASEIB |
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MV;SIAI |
Approved |
no |
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Admin @ si @ BSV2010 |
Serial |
1469 |
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Author |
Onur Ferhat; Fernando Vilariño |
![download PDF file pdf](img/file_PDF.gif)
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Title |
A Cheap Portable Eye-Tracker Solution for Common Setups |
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Conference Article |
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Year |
2013 |
Publication |
17th European Conference on Eye Movements |
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Low cost; eye-tracker; software; webcam; Raspberry Pi |
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Abstract |
We analyze the feasibility of a cheap eye-tracker where the hardware consists of a single webcam and a Raspberry Pi device. Our aim is to discover the limits of such a system and to see whether it provides an acceptable performance. We base our work on the open source Opengazer (Zielinski, 2013) and we propose several improvements to create a robust, real-time system. After assessing the accuracy of our eye-tracker in elaborated experiments involving 18 subjects under 4 different system setups, we developed a simple game to see how it performs in practice and we also installed it on a Raspberry Pi to create a portable stand-alone eye-tracker which achieves 1.62° horizontal accuracy with 3 fps refresh rate for a building cost of 70 Euros. |
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Lund; Sweden; August 2013 |
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ECEM |
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MV;SIAI |
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no |
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Admin @ si @ FeV2013 |
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2374 |
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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 |
Current Challenges on Polyp Detection in Colonoscopy Videos: From Region Segmentation to Region Classification. a Pattern Recognition-based Approach.ased Approach |
Type |
Conference Article |
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Year |
2011 |
Publication |
2nd International Workshop on Medical Image Analysis and Descriptionfor Diagnosis Systems |
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62-71 |
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Medical Imaging, Colonoscopy, Pattern Recognition, Segmentation, Polyp Detection, Region Description, Machine Learning, Real-time. |
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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. |
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Rome, Italy |
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SciTePress |
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Djemal, Khalifa |
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800 |
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MIAD |
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Notes ![sorted by Notes field, ascending order (up)](img/sort_asc.gif) |
MV;SIAI |
Approved |
no |
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Call Number |
IAM @ iam @ BSV2011a |
Serial |
1695 |
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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)
![find book details (via ISBN) isbn](img/isbn.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 |
Abbreviated Journal |
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Volume |
6669 |
Issue |
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Pages |
134-143 |
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Keywords |
Colonoscopy, Polyp Detection, Region Merging, Region Segmentation. |
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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. |
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Address |
Las Palmas de Gran Canaria, June 2011 |
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Corporate Author |
SpringerLink |
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Editor |
Vitrià, Jordi and Sanches, João and Hernández, Mario |
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Lecture Notes in Computer Science |
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LNCS |
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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 |
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Notes ![sorted by Notes field, ascending order (up)](img/sort_asc.gif) |
MV;SIAI |
Approved |
no |
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Call Number |
IAM @ iam @ BSV2011c |
Serial |
1696 |
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Permanent link to this record |
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Author |
Jorge Bernal; Fernando Vilariño; F. Javier Sanchez |
![download PDF file pdf](img/file_PDF.gif)
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Towards Intelligent Systems for Colonoscopy |
Type |
Book Chapter |
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Year |
2011 |
Publication |
Colonoscopy |
Abbreviated Journal |
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Volume |
1 |
Issue |
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Pages |
257-282 |
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Keywords |
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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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Publisher |
Intech |
Place of Publication |
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Editor |
Paul Miskovitz |
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Series Title |
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Series Issue |
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Edition |
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ISSN |
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ISBN |
978-953-307-568-6 |
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Area |
800 |
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Notes ![sorted by Notes field, ascending order (up)](img/sort_asc.gif) |
MV;SIAI |
Approved |
no |
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Call Number |
IAM @ iam @ BVS2011 |
Serial |
1697 |
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Permanent link to this record |
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Author |
Jorge Bernal; F. Javier Sanchez; Fernando Vilariño |
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Title |
Integration of Valley Orientation Distribution for Polyp Region Identification in Colonoscopy |
Type |
Conference Article |
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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 |
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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. |
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Address |
Toronto, Canada |
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Corporate Author |
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Thesis |
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Publisher |
Springer Link |
Place of Publication |
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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 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 |
ABI |
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Notes ![sorted by Notes field, ascending order (up)](img/sort_asc.gif) |
MV;SIAI |
Approved |
no |
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Call Number |
IAM @ iam @ BSV2011d |
Serial |
1698 |
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Permanent link to this record |
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Author |
Jorge Bernal; F. Javier Sanchez; Fernando Vilariño |
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Title |
Depth of Valleys Accumulation Algorithm for Object Detection |
Type |
Conference Article |
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Year |
2011 |
Publication |
14th Congrès Català en Intel·ligencia Artificial |
Abbreviated Journal |
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Volume |
1 |
Issue |
1 |
Pages |
71-80 |
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Keywords |
Object Recognition, Object Region Identification, Image Analysis, Image Processing |
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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. |
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Address |
Lleida |
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Corporate Author |
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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 |
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Notes ![sorted by Notes field, ascending order (up)](img/sort_asc.gif) |
MV;SIAI |
Approved |
no |
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Call Number |
IAM @ iam @ BSV2011b |
Serial |
1699 |
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Permanent link to this record |