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| Author | Patrick Brandao; O. Zisimopoulos; E. Mazomenos; G. Ciutib; Jorge Bernal; M. Visentini-Scarzanell; A. Menciassi; P. Dario; A. Koulaouzidis; A. Arezzo; D.J. Hawkes; D. Stoyanov | ||||
| Title | Towards a computed-aided diagnosis system in colonoscopy: Automatic polyp segmentation using convolution neural networks | Type | Journal | ||
| Year | 2018 | Publication | Journal of Medical Robotics Research | Abbreviated Journal | JMRR |
| Volume | 3 | Issue | 2 | Pages | |
| Keywords | convolutional neural networks; colonoscopy; computer aided diagnosis | ||||
| Abstract | Early diagnosis is essential for the successful treatment of bowel cancers including colorectal cancer (CRC) and capsule endoscopic imaging with robotic actuation can be a valuable diagnostic tool when combined with automated image analysis. We present a deep learning rooted detection and segmentation framework for recognizing lesions in colonoscopy and capsule endoscopy images. We restructure established convolution architectures, such as VGG and ResNets, by converting them into fully-connected convolution networks (FCNs), ne-tune them and study their capabilities for polyp segmentation and detection. We additionally use Shape-from-Shading (SfS) to recover depth and provide a richer representation of the tissue's structure in colonoscopy images. Depth is
incorporated into our network models as an additional input channel to the RGB information and we demonstrate that the resulting network yields improved performance. Our networks are tested on publicly available datasets and the most accurate segmentation model achieved a mean segmentation IU of 47.78% and 56.95% on the ETIS-Larib and CVC-Colon datasets, respectively. For polyp detection, the top performing models we propose surpass the current state of the art with detection recalls superior to 90% for all datasets tested. To our knowledge, we present the rst work to use FCNs for polyp segmentation in addition to proposing a novel combination of SfS and RGB that boosts performance. |
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| Notes | MV; no menciona | Approved | no | ||
Call Number  |
BZM2018 | Serial | 2976 | ||
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| Author | Victor Borjas; Jordi Vitria; Petia Radeva | ||||
| Title | Gradient Histogram Background Modeling for People Detection in Stationary Camera Environments | Type | Conference Article | ||
| Year | 2013 | Publication | 13th IAPR Conference on Machine Vision Applications | Abbreviated Journal | |
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| Abstract | Best Poster AwardOne of the big challenges of today person detectors is the decreasing of the false positive rate. In this paper, we propose a novel framework to customize person detectors in static camera scenarios in order to reduce this rate. This scheme includes background modeling for subtraction based on gradient histograms and Mean-Shift clustering. Our experiments show that the detection improved compared to using only the output from the pedestrian detector reducing 87% of the false positives and therefore the overall precision of the detection
was increased signi cantly. |
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| Address | Kyoto; Japan; May 2013 | ||||
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| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | MVA | ||
| Notes | OR; MILAB;MV | Approved | no | ||
| Call Number |
BVR2013 | Serial | 2238 | ||
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| Author | Fernando Barrera; Felipe Lumbreras; Angel Sappa | ||||
| Title | Evaluation of Similarity Functions in Multimodal Stereo | Type | Conference Article | ||
| Year | 2012 | Publication | 9th International Conference on Image Analysis and Recognition | Abbreviated Journal | |
| Volume | 7324 | Issue | I | Pages | 320-329 |
| Keywords | Aveiro, Portugal | ||||
| Abstract | This paper presents an evaluation framework for multimodal stereo matching, which allows to compare the performance of four similarity functions. Additionally, it presents details of a multimodal stereo head that supply thermal infrared and color images, as well as, aspects of its calibration and rectification. The pipeline includes a novel method for the disparity selection, which is suitable for evaluating the similarity functions. Finally, a benchmark for comparing different initializations of the proposed framework is presented. Similarity functions are based on mutual information, gradient orientation and scale space representations. Their evaluation is performed using two metrics: i) disparity error, and ii) number of correct matches on planar regions. In addition to the proposed evaluation, the current paper also shows that 3D sparse representations can be recovered from such a multimodal stereo head. | ||||
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-31294-6 | Medium | |
| Area | Expedition | Conference | ICIAR | ||
| Notes | ADAS | Approved | no | ||
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BLS2012a | Serial | 2014 | ||
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| Author | Dena Bazazian; Dimosthenis Karatzas; Andrew Bagdanov | ||||
| Title | Word Spotting in Scene Images based on Character Recognition | Type | Conference Article | ||
| Year | 2018 | Publication | IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops | Abbreviated Journal | |
| Volume | Issue | Pages | 1872-1874 | ||
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| Abstract | In this paper we address the problem of unconstrained Word Spotting in scene images. We train a Fully Convolutional Network to produce heatmaps of all the character classes. Then, we employ the Text Proposals approach and, via a rectangle classifier, detect the most likely rectangle for each query word based on the character attribute maps. We evaluate the proposed method on ICDAR2015 and show that it is capable of identifying and recognizing query words in natural scene images. | ||||
| Address | Salt Lake City; USA; June 2018 | ||||
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| Area | Expedition | Conference | CVPRW | ||
| Notes | DAG; 600.129; 600.121 | Approved | no | ||
| Call Number |
BKB2018a | Serial | 3179 | ||
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| Author | Thierry Brouard; Jordi Gonzalez; Caifeng Shan; Massimo Piccardi; Larry S. Davis | ||||
| Title | Special issue on background modeling for foreground detection in real-world dynamic scenes | Type | Journal Article | ||
| Year | 2014 | Publication | Machine Vision and Applications | Abbreviated Journal | MVAP |
| Volume | 25 | Issue | 5 | Pages | 1101-1103 |
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| Abstract | Although background modeling and foreground detection are not mandatory steps for computer vision applications, they may prove useful as they separate the primal objects usually called “foreground” from the remaining part of the scene called “background”, and permits different algorithmic treatment in the video processing field such as video surveillance, optical motion capture, multimedia applications, teleconferencing and human–computer interfaces. Conventional background modeling methods exploit the temporal variation of each pixel to model the background, and the foreground detection is made using change detection. The last decade witnessed very significant publications on background modeling but recently new applications in which background is not static, such as recordings taken from mobile devices or Internet videos, need new developments to detect robustly moving objects in challenging environments. Thus, effective methods for robustness to deal both with dynamic backgrounds, i | ||||
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 0932-8092 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ISE; 600.078 | Approved | no | ||
| Call Number |
BGS2014a | Serial | 2411 | ||
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| Author | Maria Vanrell; Jordi Vitria; Xavier Roca | ||||
| Title | A multidimensional scaling approach to explore the behavior of a texture perception algorithm. | Type | Journal Article | ||
| Year | 1997 | Publication | Machine Vision and Applications | Abbreviated Journal | |
| Volume | 9 | Issue | Pages | 262–271 | |
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| Notes | OR;ISE;CIC;MV | Approved | no | ||
| Call Number |
BCNPCL @ bcnpcl @ VVR1997 | Serial | 35 | ||
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| Author | Maria Vanrell; Jordi Vitria; Xavier Roca | ||||
| Title | A General Morphological Framework for Perceptual Texture Discrimination based on Granulometries. | Type | Miscellaneous | ||
| Year | 1993 | Publication | Technical Workshop on Mathematical Morphology and its Applications to Signal Processing. | Abbreviated Journal | |
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| Address | Barcelona | ||||
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| Notes | OR;ISE;CIC;MV | Approved | no | ||
| Call Number |
BCNPCL @ bcnpcl @ VVR1993 | Serial | 154 | ||
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| Author | Fernando Vilariño; Panagiota Spyridonos; Jordi Vitria; Carolina Malagelada; Petia Radeva | ||||
| Title | A Machine Learning framework using SOMs: Applications in the Intestinal Motility Assessment | Type | Book Chapter | ||
| Year | 2006 | Publication | 11th Iberoamerican Congress on Pattern Recognition | Abbreviated Journal | |
| Volume | 4225 | Issue | 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. | ||||
| Address | Cancun (Mexico) | ||||
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| Publisher | Springer Verlag | Place of Publication | Berlin-Heidelberg | Editor | J.P. Martinez–Trinidad et al |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
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| Area | 800 | Expedition | Conference | CIARP06 | |
| Notes | MV;OR;MILAB;SIAI | Approved | no | ||
| Call Number |
BCNPCL @ bcnpcl @ VSV2006d; IAM @ iam @ VSV2006e | Serial | 729 | ||
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| Author | Fernando Vilariño; Panagiota Spyridonos; Jordi Vitria; Carolina Malagelada; Petia Radeva | ||||
| Title | Linear Radial Patterns Characterization for Automatic Detection of Tonic Intestinal Contractions | Type | Book Chapter | ||
| Year | 2006 | Publication | 11th Iberoamerican Congress on Pattern Recognition | Abbreviated Journal | |
| Volume | 4225 | Issue | 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. | ||||
| Address | Cancun (Mexico) | ||||
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| Publisher | Springer Verlag | Place of Publication | Berlin Heidelberg | Editor | .F. Mart ́ınez-Trinidad et al |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
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| ISSN | ISBN | Medium | |||
| Area | 800 | Expedition | Conference | ||
| Notes | MV;OR;MILAB;SIAI | Approved | no | ||
| Call Number |
BCNPCL @ bcnpcl @ VSV2006c; IAM @ iam @ VSB2006f | Serial | 728 | ||
| Permanent link to this record | |||||
| Author | Fernando Vilariño; Panagiota Spyridonos; Jordi Vitria; Fernando Azpiroz; Petia Radeva | ||||
| Title | Automatic Detection of Intestinal Juices in Wireless Capsule Video Endoscopy | Type | Conference Article | ||
| Year | 2006 | Publication | 18th International Conference on Pattern Recognition | Abbreviated Journal | |
| Volume | 4 | Issue | Pages | 719-722 | |
| Keywords | Clinical diagnosis , Endoscopes , Fluids and secretions , Gabor filters , Hospitals , Image sequence analysis , Intestines , Lighting , Shape , Visualization | ||||
| 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. | ||||
| Address | Hong Kong | ||||
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| ISSN | 1051-4651 | ISBN | 0-7695-2521-0 | Medium | |
| Area | 800 | Expedition | Conference | ICPR | |
| Notes | MV;OR;MILAB;SIAI | Approved | no | ||
| Call Number |
BCNPCL @ bcnpcl @ VSV2006b; IAM @ iam @ VSV2006g | Serial | 727 | ||
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| Author | Fernando Vilariño; Panagiota Spyridonos; Jordi Vitria; Fernando Azpiroz; Petia Radeva | ||||
| Title | Cascade analysis for intestinal contraction detection | Type | Conference Article | ||
| Year | 2006 | Publication | 20th International Congress and exhibition Computer Assisted Radiology and Surgery | Abbreviated Journal | |
| Volume | Issue | Pages | 9-10 | ||
| Keywords | intestine video analysis, anisotropic features, support vector machine, cascade of classifiers | ||||
| Abstract | In this work, we address the study of intestinal contractions in a novel approach based on a machine learning framework to process data from Wireless Capsule Video Endoscopy. Wireless endoscopy represents a unique way to visualize the intestine motility by creating long videos to visualize intestine dynamics. In this paper we argue that to analyze huge amount of wireless endoscopy data and define robust methods for contraction detection we should base our approach on sophisticated machine learning techniques. In particular, we propose a cascade of classifiers in order to remove different physiological phenomenon and obtain the motility pattern of small intestines. Our results show obtaining high specificity and sensitivity rates that highlight the high efficiency of the selected approach and support the feasibility of the proposed methodology in the automatic detection and analysis of intestine contractions. | ||||
| Address | Osaka (Japan) | ||||
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| Area | 800 | Expedition | Conference | CARS | |
| Notes | MV;OR;MILAB;SIAI | Approved | no | ||
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BCNPCL @ bcnpcl @ VSV2006a; IAM @ iam @ VSV2006h | Serial | 726 | ||
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| Author | V. Valev; B. Sankur; Petia Radeva | ||||
| Title | Generalized Non Reducible Descriptors. | Type | Conference Article | ||
| Year | 2000 | Publication | 15 th International Conference on Pattern Recognition | Abbreviated Journal | |
| Volume | 2 | Issue | Pages | 397-397 | |
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| Address | Barcelona. | ||||
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| Area | Expedition | Conference | ICPR | ||
| Notes | MILAB | Approved | no | ||
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BCNPCL @ bcnpcl @ VSR2000 | Serial | 230 | ||
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| Author | V. Valev; B. Sankur; Petia Radeva | ||||
| Title | Generalized Non-Reducible Descriptors. | Type | Miscellaneous | ||
| Year | 1997 | Publication | Technical Report. | Abbreviated Journal | |
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| Notes | MILAB | Approved | no | ||
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BCNPCL @ bcnpcl @ VSR1997 | Serial | 65 | ||
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| Author | Fernando Vilariño; Panagiota Spyridonos; Fosca De Iorio; Jordi Vitria; Fernando Azpiroz; Petia Radeva | ||||
| Title | Intestinal Motility Assessment With Video Capsule Endoscopy: Automatic Annotation of Phasic Intestinal Contractions | Type | Journal Article | ||
| Year | 2010 | Publication | IEEE Transactions on Medical Imaging | Abbreviated Journal | TMI |
| Volume | 29 | Issue | 2 | Pages | 246-259 |
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| Abstract | Intestinal motility assessment with video capsule endoscopy arises as a novel and challenging clinical fieldwork. This technique is based on the analysis of the patterns of intestinal contractions shown in a video provided by an ingestible capsule with a wireless micro-camera. The manual labeling of all the motility events requires large amount of time for offline screening in search of findings with low prevalence, which turns this procedure currently unpractical. In this paper, we propose a machine learning system to automatically detect the phasic intestinal contractions in video capsule endoscopy, driving a useful but not feasible clinical routine into a feasible clinical procedure. Our proposal is based on a sequential design which involves the analysis of textural, color, and blob features together with SVM classifiers. Our approach tackles the reduction of the imbalance rate of data and allows the inclusion of domain knowledge as new stages in the cascade. We present a detailed analysis, both in a quantitative and a qualitative way, by providing several measures of performance and the assessment study of interobserver variability. Our system performs at 70% of sensitivity for individual detection, whilst obtaining equivalent patterns to those of the experts for density of contractions. | ||||
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| Corporate Author | IEEE | Thesis | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 0278-0062 | ISBN | Medium | ||
| Area | 800 | Expedition | Conference | ||
| Notes | MILAB;MV;OR;SIAI | Approved | no | ||
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BCNPCL @ bcnpcl @ VSD2010; IAM @ iam @ VSI2010 | Serial | 1281 | ||
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| Author | Jordi Vitria; Petia Radeva; X. Binefa; A. Pujol; Ernest Valveny; Robert Benavente; Craig Von Land | ||||
| Title | Real time recognition of pharmaceutical products by subspace methods | Type | Report | ||
| Year | 1999 | Publication | CVC Technical Report #35 | Abbreviated Journal | |
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| Address | CVC (UAB) | ||||
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| Notes | OR;MILAB;DAG;CIC;MV | Approved | no | ||
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BCNPCL @ bcnpcl @ VRB1999b | Serial | 54 | ||
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