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Author  |
Jorge Bernal; F. Javier Sanchez; Fernando Vilariño |
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Title |
Impact of Image Preprocessing Methods on Polyp Localization in Colonoscopy Frames |
Type |
Conference Article |
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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 |
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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. |
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Osaka; Japan; July 2013 |
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ISSN |
1557-170X |
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800 |
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Conference |
EMBC |
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Notes |
MV; 600.047; 600.060;SIAI |
Approved |
no |
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Call Number |
Admin @ si @ BSV2013 |
Serial |
2286 |
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Author |
Jorge Bernal; F. Javier Sanchez; Fernando Vilariño |
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Title |
Towards Automatic Polyp Detection with a Polyp Appearance Model |
Type |
Journal Article |
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Year |
2012 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
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Volume |
45 |
Issue |
9 |
Pages |
3166-3182 |
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Keywords |
Colonoscopy,PolypDetection,RegionSegmentation,SA-DOVA descriptot |
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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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Elsevier |
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ISSN |
0031-3203 |
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800 |
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Conference |
IbPRIA |
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Notes |
MV;SIAI |
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no |
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Call Number |
Admin @ si @ BSV2012; IAM @ iam |
Serial |
1997 |
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Author |
Jorge Bernal; F. Javier Sanchez; Cristina Rodriguez de Miguel; Gloria Fernandez Esparrach |
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Title |
Bulding up the future of colonoscopy: A synergy between clinicians and computer scientists |
Type |
Book Chapter |
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Year |
2015 |
Publication |
Colonoscopy and Colorectal Cancer |
Abbreviated Journal |
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Keywords |
Intelligent systems; Image properties; Validation; Clinical drawbacks; Endoluminal scene description |
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Abstract |
Recent advances in endoscopic technology have generated an increasing interest in strengthening the collaboration between clinicians and computers scientist to develop intelligent systems that can provide additional information to clinicians in the different stages of an intervention. The objective of this chapter is to identify clinical drawbacks of colonoscopy in order to define potential areas of collaboration. Once areas are defined, we present the challenges that colonoscopy images present in order computational methods to provide with meaningful output, including those related to image formation and acquisition, as they are proven to have an impact in the performance of an intelligent system. Finally, we also propose how to define validation frameworks in order to assess the performance of a given method, making an special emphasis on how databases should be created and annotated and which metrics should be used to evaluate systems correctly. |
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978-953-51-2225-8 |
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Notes |
MV |
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no |
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Call Number |
Admin @ si @ BSR2015 |
Serial |
2624 |
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Author |
Jorge Bernal; Debora Gil; Carles Sanchez; F. Javier Sanchez |
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Title |
Discarding Non Informative Regions for Efficient Colonoscopy Image Analysis |
Type |
Conference Article |
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Year |
2014 |
Publication |
1st MICCAI Workshop on Computer-Assisted and Robotic Endoscopy |
Abbreviated Journal |
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Volume |
8899 |
Issue |
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Pages |
1-10 |
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Keywords |
Image Segmentation; Polyps, Colonoscopy; Valley Information; Energy Maps |
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Abstract |
In this paper we present a novel polyp region segmentation method for colonoscopy videos. Our method uses valley information associated to polyp boundaries in order to provide an initial segmentation. This first segmentation is refined to eliminate boundary discontinuities caused by image artifacts or other elements of the scene. Experimental results over a publicly annotated database show that our method outperforms both general and specific segmentation methods by providing more accurate regions rich in polyp content. We also prove how image preprocessing is needed to improve final polyp region segmentation. |
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Boston; USA; September 2014 |
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Springer International Publishing |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-319-13409-3 |
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Conference |
CARE |
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Notes |
MV; IAM; 600.044; 600.047; 600.060; 600.075 |
Approved |
no |
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Call Number |
Admin @ si @ BGS2014b |
Serial |
2503 |
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Author |
Jorge Bernal; David Vazquez (eds) |
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Title |
Computer vision Trends and Challenges |
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Book Whole |
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Year |
2013 |
Publication |
Computer vision Trends and Challenges |
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Keywords |
CVCRD; Computer Vision |
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Abstract |
This book contains the papers presented at the Eighth CVC Workshop on Computer Vision Trends and Challenges (CVCR&D'2013). The workshop was held at the Computer Vision Center (Universitat Autònoma de Barcelona), the October 25th, 2013. The CVC workshops provide an excellent opportunity for young researchers and project engineers to share new ideas and knowledge about the progress of their work, and also, to discuss about challenges and future perspectives. In addition, the workshop is the welcome event for new people that recently have joined the institute.
The program of CVCR&D is organized in a single-track single-day workshop. It comprises several sessions dedicated to specific topics. For each session, a doctor working on the topic introduces the general research lines. The PhD students expose their specific research. A poster session will be held for open questions. Session topics cover the current research lines and development projects of the CVC: Medical Imaging, Medical Imaging, Color & Texture Analysis, Object Recognition, Image Sequence Evaluation, Advanced Driver Assistance Systems, Machine Vision, Document Analysis, Pattern Recognition and Applications. We want to thank all paper authors and Program Committee members. Their contribution shows that the CVC has a dynamic, active, and promising scientific community.
We hope you all enjoy this Eighth workshop and we are looking forward to meeting you and new people next year in the Ninth CVCR&D. |
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Jorge Bernal; David Vazquez |
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978-84-940902-2-6 |
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no |
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Call Number |
ADAS @ adas @ BeV2013 |
Serial |
2339 |
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Author |
Jorge Bernal; Aymeric Histace; Marc Masana; Quentin Angermann; Cristina Sanchez Montes; Cristina Rodriguez de Miguel; Maroua Hammami; Ana Garcia Rodriguez; Henry Cordova; Olivier Romain; Gloria Fernandez Esparrach; Xavier Dray; F. Javier Sanchez |
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Title |
Polyp Detection Benchmark in Colonoscopy Videos using GTCreator: A Novel Fully Configurable Tool for Easy and Fast Annotation of Image Databases |
Type |
Conference Article |
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Year |
2018 |
Publication |
32nd International Congress and Exhibition on Computer Assisted Radiology & Surgery |
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CARS |
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Notes |
ISE; MV; 600.119 |
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no |
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Call Number |
Admin @ si @ BHM2018 |
Serial |
3089 |
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Author |
Jorge Bernal; Aymeric Histace; Marc Masana; Quentin Angermann; Cristina Sanchez Montes; Cristina Rodriguez de Miguel; Maroua Hammami; Ana Garcia Rodriguez; Henry Cordova; Olivier Romain; Gloria Fernandez Esparrach; Xavier Dray; F. Javier Sanchez |
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Title |
GTCreator: a flexible annotation tool for image-based datasets |
Type |
Journal Article |
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Year |
2019 |
Publication |
International Journal of Computer Assisted Radiology and Surgery |
Abbreviated Journal |
IJCAR |
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Volume |
14 |
Issue |
2 |
Pages |
191–201 |
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Keywords |
Annotation tool; Validation Framework; Benchmark; Colonoscopy; Evaluation |
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Abstract |
Abstract Purpose: Methodology evaluation for decision support systems for health is a time consuming-task. To assess performance of polyp detection
methods in colonoscopy videos, clinicians have to deal with the annotation
of thousands of images. Current existing tools could be improved in terms of
exibility and ease of use. Methods:We introduce GTCreator, a exible annotation tool for providing image and text annotations to image-based datasets.
It keeps the main basic functionalities of other similar tools while extending
other capabilities such as allowing multiple annotators to work simultaneously
on the same task or enhanced dataset browsing and easy annotation transfer aiming to speed up annotation processes in large datasets. Results: The
comparison with other similar tools shows that GTCreator allows to obtain
fast and precise annotation of image datasets, being the only one which offers
full annotation editing and browsing capabilites. Conclusions: Our proposed
annotation tool has been proven to be efficient for large image dataset annota-
tion, as well as showing potential of use in other stages of method evaluation
such as experimental setup or results analysis. |
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Notes |
MV; 600.096; 600.109; 600.119; 601.305 |
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no |
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Call Number |
Admin @ si @ BHM2019 |
Serial |
3163 |
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Author |
Jorge Bernal |
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Title |
Use of Projection and Back-projection Methods in Bidimensional Computed Tomography Image Reconstruction |
Type |
Report |
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Year |
2009 |
Publication |
CVC Tecnical Report |
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141 |
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Pages |
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Keywords |
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 |
Computer Vision Center |
Thesis |
Master's thesis |
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Place of Publication |
Barcelona, Spain |
Editor |
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Area |
800 |
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Notes |
MV; |
Approved |
no |
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Call Number |
IAM @ iam @ Ber2009 |
Serial |
1693 |
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Author |
Jorge Bernal |
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Title |
Polyp Localization and Segmentation in Colonoscopy Images by Means of a Model of Appearance for Polyps |
Type |
Book Whole |
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Year |
2012 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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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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Thesis |
Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
Place of Publication |
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Editor |
F. Javier Sanchez;Fernando Vilariño |
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800 |
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Notes |
MV |
Approved |
no |
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Call Number |
Admin @ si @ Ber2012 |
Serial |
2211 |
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Author |
Jorge Bernal |
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Title |
Polyp Localization and Segmentation in Colonoscopy Images by Means of a Model of Appearance for Polyps |
Type |
Journal Article |
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Year |
2014 |
Publication |
Electronic Letters on Computer Vision and Image Analysis |
Abbreviated Journal |
ELCVIA |
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Volume |
13 |
Issue |
2 |
Pages |
9-10 |
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Keywords |
Colonoscopy; polyp localization; polyp segmentation; Eye-tracking |
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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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Editor |
Alicia Fornes; Volkmar Frinken |
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MV |
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Call Number |
Admin @ si @ Ber2014 |
Serial |
2487 |
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Author |
Jordy Van Landeghem; Ruben Tito; Lukasz Borchmann; Michal Pietruszka; Pawel Joziak; Rafal Powalski; Dawid Jurkiewicz; Mickael Coustaty; Bertrand Anckaert; Ernest Valveny; Matthew Blaschko; Sien Moens; Tomasz Stanislawek |
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Title |
Document Understanding Dataset and Evaluation (DUDE) |
Type |
Conference Article |
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Year |
2023 |
Publication |
20th IEEE International Conference on Computer Vision |
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Pages |
19528-19540 |
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Abstract |
We call on the Document AI (DocAI) community to re-evaluate current methodologies and embrace the challenge of creating more practically-oriented benchmarks. Document Understanding Dataset and Evaluation (DUDE) seeks to remediate the halted research progress in understanding visually-rich documents (VRDs). We present a new dataset with novelties related to types of questions, answers, and document layouts based on multi-industry, multi-domain, and multi-page VRDs of various origins and dates. Moreover, we are pushing the boundaries of current methods by creating multi-task and multi-domain evaluation setups that more accurately simulate real-world situations where powerful generalization and adaptation under low-resource settings are desired. DUDE aims to set a new standard as a more practical, long-standing benchmark for the community, and we hope that it will lead to future extensions and contributions that address real-world challenges. Finally, our work illustrates the importance of finding more efficient ways to model language, images, and layout in DocAI. |
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Paris; France; October 2023 |
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ICCV |
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Notes |
DAG |
Approved |
no |
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Call Number |
Admin @ si @ LTB2023 |
Serial |
3948 |
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Author |
Jordina Torrents-Barrena; Aida Valls; Petia Radeva; Meritxell Arenas; Domenec Puig |
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Title |
Automatic Recognition of Molecular Subtypes of Breast Cancer in X-Ray images using Segmentation-based Fractal Texture Analysis |
Type |
Book Chapter |
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Year |
2015 |
Publication |
Artificial Intelligence Research and Development |
Abbreviated Journal |
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Volume |
277 |
Issue |
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Pages |
247 - 256 |
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Abstract |
Breast cancer disease has recently been classified into four subtypes regarding the molecular properties of the affected tumor region. For each patient, an accurate diagnosis of the specific type is vital to decide the most appropriate therapy in order to enhance life prospects. Nowadays, advanced therapeutic diagnosis research is focused on gene selection methods, which are not robust enough. Hence, we hypothesize that computer vision algorithms can offer benefits to address the problem of discriminating among them through X-Ray images. In this paper, we propose a novel approach driven by texture feature descriptors and machine learning techniques. First, we segment the tumour part through an active contour technique and then, we perform a complete fractal analysis to collect qualitative information of the region of interest in the feature extraction stage. Finally, several supervised and unsupervised classifiers are used to perform multiclass classification of the aforementioned data. The experimental results presented in this paper support that it is possible to establish a relation between each tumor subtype and the extracted features of the patterns revealed on mammograms. |
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IOS Press |
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Frontiers in Artificial Intelligence and Applications |
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MILAB |
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Admin @ si @TVR2015 |
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2780 |
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Author |
Jordi Vitria; X. Binefa; Juan J. Villanueva |
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Title |
Morphological Algorithms for Visual Analysis of Integrated Circuits. |
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Miscellaneous |
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Year |
1992 |
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Journal of Visual Communications and image Representation, Vol.3, No.2, pp.194–202. |
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OR;MV |
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BCNPCL @ bcnpcl @ VBV1992 |
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248 |
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Author |
Jordi Vitria; Petia Radeva; X. Binefa; A. Pujol; Ernest Valveny; Robert Benavente; Craig Von Land |
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Title |
Real time recognition of pharmaceutical products by subspace methods |
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Report |
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1999 |
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CVC Technical Report #35 |
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OR;MILAB;DAG;CIC;MV |
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no |
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BCNPCL @ bcnpcl @ VRB1999b |
Serial |
54 |
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Author |
Jordi Vitria; Petia Radeva; X. Binefa |
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Title |
EigenHistograms: using low dimensional models of color distribution for real time object recognition |
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1999 |
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Ljubliana, Slovenia, Springer-Verlag |
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Notes |
OR;MILAB;MV |
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no |
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Call Number |
BCNPCL @ bcnpcl @ VRB1999a |
Serial |
29 |
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