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Mirko Arnold; Anarta Ghosh; Glen Doherty; Hugh Mulcahy; Stephen Patchett; Gerard Lacey |
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Title |
Towards Automatic Direct Observation of Procedure and Skill (DOPS) in Colonoscopy |
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Conference Article |
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2013 |
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Proceedings of the International Conference on Computer Vision Theory and Applications |
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48-53 |
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VISIGRAPP |
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fernando @ fernando @ |
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2427 |
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Author |
Jorge Bernal |
![download PDF file pdf](img/file_PDF.gif)
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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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13 |
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2 |
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9-10 |
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Colonoscopy; polyp localization; polyp segmentation; Eye-tracking |
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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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Alicia Fornes; Volkmar Frinken |
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Admin @ si @ Ber2014 |
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2487 |
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Author |
Jorge Bernal; F. Javier Sanchez; Cristina Rodriguez de Miguel; Gloria Fernandez Esparrach |
![goto web page url](img/www.gif)
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Title |
Bulding up the future of colonoscopy: A synergy between clinicians and computer scientists |
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Book Chapter |
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2015 |
Publication |
Colonoscopy and Colorectal Cancer |
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Intelligent systems; Image properties; Validation; Clinical drawbacks; Endoluminal scene description |
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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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Admin @ si @ BSR2015 |
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2624 |
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Author |
Joan M. Nuñez |
![find book details (via ISBN) isbn](img/isbn.gif)
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Title |
Vascular Pattern Characterization in Colonoscopy Images |
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Book Whole |
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Year |
2015 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Colorectal cancer is the third most common cancer worldwide and the second most common malignant tumor in Europe. Screening tests have shown to be very eective in increasing the survival rates since they allow an early detection of polyps. Among the dierent screening techniques, colonoscopy is considered the gold standard although clinical studies mention several problems that have an impact in the quality of the procedure. The navigation through the rectum and colon track can be challenging for the physicians which can increase polyp miss rates. The thorough visualization of the colon track must be ensured so that
the chances of missing lesions are minimized. The visual analysis of colonoscopy images can provide important information to the physicians and support their navigation during the procedure.
Blood vessels and their branching patterns can provide descriptive power to potentially develop biometric markers. Anatomical markers based on blood vessel patterns could be used to identify a particular scene in colonoscopy videos and to support endoscope navigation by generating a sequence of ordered scenes through the dierent colon sections. By verifying the presence of vascular content in the endoluminal scene it is also possible to certify a proper
inspection of the colon mucosa and to improve polyp localization. Considering the potential uses of blood vessel description, this contribution studies the characterization of the vascular content and the analysis of the descriptive power of its branching patterns.
Blood vessel characterization in colonoscopy images is shown to be a challenging task. The endoluminal scene is conformed by several elements whose similar characteristics hinder the development of particular models for each of them. To overcome such diculties we propose the use of the blood vessel branching characteristics as key features for pattern description. We present a model to characterize junctions in binary patterns. The implementation
of the junction model allows us to develop a junction localization method. We
created two data sets including manually labeled vessel information as well as manual ground truths of two types of keypoint landmarks: junctions and endpoints. The proposed method outperforms the available algorithms in the literature in experiments in both, our newly created colon vessel data set, and in DRIVE retinal fundus image data set. In the latter case, we created a manual ground truth of junction coordinates. Since we want to explore the descriptive potential of junctions and vessels, we propose a graph-based approach to
create anatomical markers. In the context of polyp localization, we present a new method to inhibit the in uence of blood vessels in the extraction valley-prole information. The results show that our methodology decreases vessel in
uence, increases polyp information and leads to an improvement in state-of-the-art polyp localization performance. We also propose a polyp-specic segmentation method that outperforms other general and specic approaches. |
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November 2015 |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Editor |
Fernando Vilariño |
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978-84-943427-6-9 |
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no |
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Admin @ si @ Nuñ2015 |
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2709 |
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Author |
Onur Ferhat |
![find book details (via ISBN) isbn](img/isbn.gif)
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Title |
Analysis of Head-Pose Invariant, Natural Light Gaze Estimation Methods |
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2017 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Eye tracker devices have traditionally been only used inside laboratories, requiring trained professionals and elaborate setup mechanisms. However, in the recent years the scientific work on easier–to–use eye trackers which require no special hardware—other than the omnipresent front facing cameras in computers, tablets, and mobiles—is aiming at making this technology common–place. These types of trackers have several extra challenges that make the problem harder, such as low resolution images provided by a regular webcam, the changing ambient lighting conditions, personal appearance differences, changes in head pose, and so on. Recent research in the field has focused on all these challenges in order to provide better gaze estimation performances in a real world setup.
In this work, we aim at tackling the gaze tracking problem in a single camera setup. We first analyze all the previous work in the field, identifying the strengths and weaknesses of each tried idea. We start our work on the gaze tracker with an appearance–based gaze estimation method, which is the simplest idea that creates a direct mapping between a rectangular image patch extracted around the eye in a camera image, and the gaze point (or gaze direction). Here, we do an extensive analysis of the factors that affect the performance of this tracker in several experimental setups, in order to address these problems in future works. In the second part of our work, we propose a feature–based gaze estimation method, which encodes the eye region image into a compact representation. We argue that this type of representation is better suited to dealing with head pose and lighting condition changes, as it both reduces the dimensionality of the input (i.e. eye image) and breaks the direct connection between image pixel intensities and the gaze estimation. Lastly, we use a face alignment algorithm to have robust face pose estimation, using a 3D model customized to the subject using the tracker. We combine this with a convolutional neural network trained on a large dataset of images to build a face pose invariant gaze tracker. |
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September 2017 |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Editor |
Fernando Vilariño |
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978-84-945373-5-6 |
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Admin @ si @ Fer2017 |
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3018 |
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Author |
Jorge Bernal |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Use of Projection and Back-projection Methods in Bidimensional Computed Tomography Image Reconstruction |
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Report |
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2009 |
Publication |
CVC Tecnical Report |
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141 |
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Projection, Back-projection, CT scan, Euclidean geometry, Radon transform |
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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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Computer Vision Center |
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Master's thesis |
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Barcelona, Spain |
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MV; |
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IAM @ iam @ Ber2009 |
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1693 |
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Author |
Gloria Fernandez Esparrach; Jorge Bernal; Maria Lopez Ceron; Henry Cordova; Cristina Sanchez Montes; Cristina Rodriguez de Miguel; F. Javier Sanchez |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Exploring the clinical potential of an automatic colonic polyp detection method based on the creation of energy maps |
Type |
Journal Article |
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Year |
2016 |
Publication |
Endoscopy |
Abbreviated Journal |
END |
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Volume |
48 |
Issue |
9 |
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837-842 |
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Background and aims: Polyp miss-rate is a drawback of colonoscopy that increases significantly in small polyps. We explored the efficacy of an automatic computer vision method for polyp detection.
Methods: Our method relies on a model that defines polyp boundaries as valleys of image intensity. Valley information is integrated into energy maps which represent the likelihood of polyp presence.
Results: In 24 videos containing polyps from routine colonoscopies, all polyps were detected in at least one frame. Mean values of the maximum of energy map were higher in frames with polyps than without (p<0.001). Performance improved in high quality frames (AUC= 0.79, 95%CI: 0.70-0.87 vs 0.75, 95%CI: 0.66-0.83). Using 3.75 as maximum threshold value, sensitivity and specificity for detection of polyps were 70.4% (95%CI: 60.3-80.8) and 72.4% (95%CI: 61.6-84.6), respectively.
Conclusion: Energy maps showed a good performance for colonic polyp detection. This indicates a potential applicability in clinical practice. |
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Admin @ si @FBL2016 |
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Author |
Cristina Sanchez Montes; Jorge Bernal; Ana Garcia Rodriguez; Henry Cordova; Gloria Fernandez Esparrach |
![goto web page url](img/www.gif)
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Title |
Revisión de métodos computacionales de detección y clasificación de pólipos en imagen de colonoscopia |
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Journal Article |
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2020 |
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Gastroenterología y Hepatología |
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GH |
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43 |
Issue |
4 |
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222-232 |
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Computer-aided diagnosis (CAD) is a tool with great potential to help endoscopists in the tasks of detecting and histologically classifying colorectal polyps. In recent years, different technologies have been described and their potential utility has been increasingly evidenced, which has generated great expectations among scientific societies. However, most of these works are retrospective and use images of different quality and characteristics which are analysed off line. This review aims to familiarise gastroenterologists with computational methods and the particularities of endoscopic imaging, which have an impact on image processing analysis. Finally, the publicly available image databases, needed to compare and confirm the results obtained with different methods, are presented. |
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Admin @ si @ SBG2020 |
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3404 |
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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 |
Impact of Image Preprocessing Methods on Polyp Localization in Colonoscopy Frames |
Type |
Conference Article |
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2013 |
Publication |
35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society |
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7350 - 7354 |
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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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1557-170X |
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EMBC |
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MV; 600.047; 600.060;SIAI |
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Admin @ si @ BSV2013 |
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2286 |
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Author |
Jorge Bernal; Fernando Vilariño; F. Javier Sanchez; M. Arnold; Anarta Ghosh; Gerard Lacey |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Experts vs Novices: Applying Eye-tracking Methodologies in Colonoscopy Video Screening for Polyp Search |
Type |
Conference Article |
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2014 |
Publication |
2014 Symposium on Eye Tracking Research and Applications |
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223-226 |
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We present in this paper a novel study aiming at identifying the differences in visual search patterns between physicians of diverse levels of expertise during the screening of colonoscopy videos. Physicians were clustered into two groups -experts and novices- according to the number of procedures performed, and fixations were captured by an eye-tracker device during the task of polyp search in different video sequences. These fixations were integrated into heat maps, one for each cluster. The obtained maps were validated over a ground truth consisting of a mask of the polyp, and the comparison between experts and novices was performed by using metrics such as reaction time, dwelling time and energy concentration ratio. Experimental results show a statistically significant difference between experts and novices, and the obtained maps show to be a useful tool for the characterisation of the behaviour of each group. |
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USA; March 2014 |
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978-1-4503-2751-0 |
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ETRA |
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MV; 600.047; 600.060;SIAI |
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Admin @ si @ BVS2014 |
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2448 |
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Author |
Joan M. Nuñez; Jorge Bernal; F. Javier Sanchez; Fernando Vilariño |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Blood Vessel Characterization in Colonoscopy Images to Improve Polyp Localization |
Type |
Conference Article |
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Year |
2013 |
Publication |
Proceedings of the International Conference on Computer Vision Theory and Applications |
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1 |
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162-171 |
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Colonoscopy; Blood vessel; Linear features; Valley detection |
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This paper presents an approach to mitigate the contribution of blood vessels to the energy image used at different tasks of automatic colonoscopy image analysis. This goal is achieved by introducing a characterization of endoluminal scene objects which allows us to differentiate between the trace of 2-dimensional visual objects,such as vessels, and shades from 3-dimensional visual objects, such as folds. The proposed characterization is based on the influence that the object shape has in the resulting visual feature, and it leads to the development of a blood vessel attenuation algorithm. A database consisting of manually labelled masks was built in order to test the performance of our method, which shows an encouraging success in blood vessel mitigation while keeping other structures intact. Moreover, by extending our method to the only available polyp localization
algorithm tested on a public database, blood vessel mitigation proved to have a positive influence on the overall performance. |
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Barcelona; February 2013 |
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SciTePress |
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VISIGRAPP |
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MV; 600.054; 600.057;SIAI |
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IAM @ iam @ NBS2013 |
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2198 |
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Author |
Jorge Bernal; Joan M. Nuñez; F. Javier Sanchez; Fernando Vilariño |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Polyp Segmentation Method in Colonoscopy Videos by means of MSA-DOVA Energy Maps Calculation |
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Conference Article |
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2014 |
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3rd MICCAI Workshop on Clinical Image-based Procedures: Translational Research in Medical Imaging |
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8680 |
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41-49 |
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Image segmentation; Polyps; Colonoscopy; Valley information; Energy maps |
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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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MV; 600.060; 600.044; 600.047;SIAI |
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no |
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Admin @ si @ BNS2014 |
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2502 |
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Author |
Jorge Bernal; Nima Tajkbaksh; F. Javier Sanchez; Bogdan J. Matuszewski; Hao Chen; Lequan Yu; Quentin Angermann; Olivier Romain; Bjorn Rustad; Ilangko Balasingham; Konstantin Pogorelov; Sungbin Choi; Quentin Debard; Lena Maier Hein; Stefanie Speidel; Danail Stoyanov; Patrick Brandao; Henry Cordova; Cristina Sanchez Montes; Suryakanth R. Gurudu; Gloria Fernandez Esparrach; Xavier Dray; Jianming Liang; Aymeric Histace |
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Title |
Comparative Validation of Polyp Detection Methods in Video Colonoscopy: Results from the MICCAI 2015 Endoscopic Vision Challenge |
Type |
Journal Article |
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Year |
2017 |
Publication |
IEEE Transactions on Medical Imaging |
Abbreviated Journal |
TMI |
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36 |
Issue |
6 |
Pages |
1231 - 1249 |
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Keywords |
Endoscopic vision; Polyp Detection; Handcrafted features; Machine Learning; Validation Framework |
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Colonoscopy is the gold standard for colon cancer screening though still some polyps are missed, thus preventing early disease detection and treatment. Several computational systems have been proposed to assist polyp detection during colonoscopy but so far without consistent evaluation. The lack
of publicly available annotated databases has made it difficult to compare methods and to assess if they achieve performance levels acceptable for clinical use. The Automatic Polyp Detection subchallenge, conducted as part of the Endoscopic Vision Challenge (http://endovis.grand-challenge.org) at the international conference on Medical Image Computing and Computer Assisted
Intervention (MICCAI) in 2015, was an effort to address this need. In this paper, we report the results of this comparative evaluation of polyp detection methods, as well as describe additional experiments to further explore differences between methods. We define performance metrics and provide evaluation databases that allow comparison of multiple methodologies. Results show that convolutional neural networks (CNNs) are the state of the art. Nevertheless it is also demonstrated that combining different methodologies can lead to an improved overall performance. |
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MV; 600.096; 600.075 |
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no |
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Admin @ si @ BTS2017 |
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2949 |
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Author |
Quentin Angermann; Jorge Bernal; Cristina Sanchez Montes; Gloria Fernandez Esparrach; Xavier Gray; Olivier Romain; F. Javier Sanchez; Aymeric Histace |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Towards Real-Time Polyp Detection in Colonoscopy Videos: Adapting Still Frame-Based Methodologies for Video Sequences Analysis |
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Conference Article |
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2017 |
Publication |
4th International Workshop on Computer Assisted and Robotic Endoscopy |
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29-41 |
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Polyp detection; colonoscopy; real time; spatio temporal coherence |
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Colorectal cancer is the second cause of cancer death in United States: precursor lesions (polyps) detection is key for patient survival. Though colonoscopy is the gold standard screening tool, some polyps are still missed. Several computational systems have been proposed but none of them are used in the clinical room mainly due to computational constraints. Besides, most of them are built over still frame databases, decreasing their performance on video analysis due to the lack of output stability and not coping with associated variability on image quality and polyp appearance. We propose a strategy to adapt these methods to video analysis by adding a spatio-temporal stability module and studying a combination of features to capture polyp appearance variability. We validate our strategy, incorporated on a real-time detection method, on a public video database. Resulting method detects all
polyps under real time constraints, increasing its performance due to our
adaptation strategy. |
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Quebec; Canada; September 2017 |
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MV; 600.096; 600.075 |
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Admin @ si @ ABS2017b |
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2977 |
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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 |
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Journal Article |
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2019 |
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International Journal of Computer Assisted Radiology and Surgery |
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IJCAR |
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14 |
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2 |
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191–201 |
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Annotation tool; Validation Framework; Benchmark; Colonoscopy; Evaluation |
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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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MV; 600.096; 600.109; 600.119; 601.305 |
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Admin @ si @ BHM2019 |
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3163 |
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