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Author P. Canals; Simone Balocco; O. Diaz; J. Li; A. Garcia Tornel; M. Olive Gadea; M. Ribo
Title A fully automatic method for vascular tortuosity feature extraction in the supra-aortic region: unraveling possibilities in stroke treatment planning Type Journal Article
Year 2023 Publication (down) Computerized Medical Imaging and Graphics Abbreviated Journal CMIG
Volume 104 Issue 102170 Pages
Keywords Artificial intelligence; Deep learning; Stroke; Thrombectomy; Vascular feature extraction; Vascular tortuosity
Abstract Vascular tortuosity of supra-aortic vessels is widely considered one of the main reasons for failure and delays in endovascular treatment of large vessel occlusion in patients with acute ischemic stroke. Characterization of tortuosity is a challenging task due to the lack of objective, robust and effective analysis tools. We present a fully automatic method for arterial segmentation, vessel labelling and tortuosity feature extraction applied to the supra-aortic region. A sample of 566 computed tomography angiography scans from acute ischemic stroke patients (aged 74.8 ± 12.9, 51.0% females) were used for training, validation and testing of a segmentation module based on a U-Net architecture (162 cases) and a vessel labelling module powered by a graph U-Net (566 cases). Successively, 30 cases were processed for testing of a tortuosity feature extraction module. Measurements obtained through automatic processing were compared to manual annotations from two observers for a thorough validation of the method. The proposed feature extraction method presented similar performance to the inter-rater variability observed in the measurement of 33 geometrical and morphological features of the arterial anatomy in the supra-aortic region. This system will contribute to the development of more complex models to advance the treatment of stroke by adding immediate automation, objectivity, repeatability and robustness to the vascular tortuosity characterization of patients.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes MILAB Approved no
Call Number Admin @ si @ CBD2023 Serial 4005
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Author Debora Gil; F. Javier Sanchez; Gloria Fernandez Esparrach; Jorge Bernal
Title 3D Stable Spatio-temporal Polyp Localization in Colonoscopy Videos Type Book Chapter
Year 2015 Publication (down) Computer-Assisted and Robotic Endoscopy. Revised selected papers of Second International Workshop, CARE 2015, Held in Conjunction with MICCAI 2015 Abbreviated Journal
Volume 9515 Issue Pages 140-152
Keywords Colonoscopy, Polyp Detection, Polyp Localization, Region Extraction, Watersheds
Abstract Computational intelligent systems could reduce polyp miss rate in colonoscopy for colon cancer diagnosis and, thus, increase the efficiency of the procedure. One of the main problems of existing polyp localization methods is a lack of spatio-temporal stability in their response. We propose to explore the response of a given polyp localization across temporal windows in order to select
those image regions presenting the highest stable spatio-temporal response.
Spatio-temporal stability is achieved by extracting 3D watershed regions on the
temporal window. Stability in localization response is statistically determined by analysis of the variance of the output of the localization method inside each 3D region. We have explored the benefits of considering spatio-temporal stability in two different tasks: polyp localization and polyp detection. Experimental results indicate an average improvement of 21:5% in polyp localization and 43:78% in polyp detection.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference CARE
Notes IAM; MV; 600.075 Approved no
Call Number Admin @ si @ GSF2015 Serial 2733
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Author Partha Pratim Roy; Umapada Pal; Josep Llados
Title Recognition of Multi-oriented Touching Characters in Graphical Documents Type Conference Article
Year 2008 Publication (down) Computer Vision, Graphics & Image Processing, 2008. Sixth Indian Conference on, Abbreviated Journal
Volume 16 Issue Pages 297–304
Keywords
Abstract
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference ICVGIP ’08
Notes DAG Approved no
Call Number DAG @ dag @ RPL2008c Serial 1080
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Author Jorge Bernal; David Vazquez (eds)
Title Computer vision Trends and Challenges Type Book Whole
Year 2013 Publication (down) Computer vision Trends and Challenges Abbreviated Journal
Volume Issue Pages
Keywords CVCRD; Computer Vision
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.
Address
Corporate Author Thesis
Publisher Place of Publication Editor Jorge Bernal; David Vazquez
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-84-940902-2-6 Medium
Area Expedition Conference
Notes Approved no
Call Number ADAS @ adas @ BeV2013 Serial 2339
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Author Xavier Baro; Jordi Vitria
Title Weighted Dissociated Diploes: An Extended Visual Feature Set Type Book Chapter
Year 2008 Publication (down) Computer Vision Systems. 6th International Conference ICVS Abbreviated Journal
Volume 5008 Issue Pages 281–290
Keywords
Abstract
Address Santorini (Greece)
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes OR;HuPBA;MV Approved no
Call Number BCNPCL @ bcnpcl @ BaV2008b Serial 977
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Author Sergio Escalera; Oriol Pujol; Petia Radeva
Title Sub-Class Error-Correcting Output Codes Type Book Chapter
Year 2008 Publication (down) Computer Vision Systems. 6th International Conference Abbreviated Journal
Volume 5008 Issue Pages 494–504
Keywords
Abstract
Address Santorini (Greece)
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference ICVS
Notes MILAB;HuPBA Approved no
Call Number BCNPCL @ bcnpcl @ EPR2008c Serial 963
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Author Santiago Segui; Laura Igual; Fernando Vilariño; Petia Radeva; Carolina Malagelada; Fernando Azpiroz; Jordi Vitria
Title Diagnostic System for Intestinal Motility Disfunctions Using Video Capsule Endoscopy Type Book Chapter
Year 2008 Publication (down) Computer Vision Systems. 6th International Abbreviated Journal
Volume 5008 Issue Pages 251–260
Keywords
Abstract Wireless Video Capsule Endoscopy is a clinical technique consisting of the analysis of images from the intestine which are pro- vided by an ingestible device with a camera attached to it. In this paper we propose an automatic system to diagnose severe intestinal motility disfunctions using the video endoscopy data. The system is based on the application of computer vision techniques within a machine learn- ing framework in order to obtain the characterization of diverse motil- ity events from video sequences. We present experimental results that demonstrate the effectiveness of the proposed system and compare them with the ground-truth provided by the gastroenterologists.
Address Santorini (Greece)
Corporate Author Thesis
Publisher Springer-Verlag Place of Publication Berlin Heidelberg Editor A. Gasteratos, M. Vincze, and J.K. Tsotsos
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN 978-3-540-79546-9 Medium
Area 800 Expedition Conference ICVS
Notes OR; MV; MILAB; SIAI Approved no
Call Number BCNPCL @ bcnpcl @ SIV2008; IAM @ iam @ SIV2008 Serial 962
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Author Antonio Lopez
Title Ridge/Valley-like structures: Creases, separatrices and drainage patterns Type Miscellaneous
Year 1997 Publication (down) Computer vision on–line Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address CVC
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes ADAS Approved no
Call Number ADAS @ adas @ Lop1997 Serial 488
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Author David Geronimo; David Vazquez; Arturo de la Escalera
Title Vision-Based Advanced Driver Assistance Systems Type Book Chapter
Year 2017 Publication (down) Computer Vision in Vehicle Technology: Land, Sea, and Air Abbreviated Journal
Volume Issue Pages
Keywords ADAS; Autonomous Driving
Abstract
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes ADAS; 600.118 Approved no
Call Number ADAS @ adas @ GVE2017 Serial 2881
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Author Antonio Lopez; Atsushi Imiya; Tomas Pajdla; Jose Manuel Alvarez
Title Computer Vision in Vehicle Technology: Land, Sea & Air Type Book Whole
Year Publication (down) Computer Vision in Vehicle Technology: Land, Sea & Air Abbreviated Journal
Volume Issue Pages
Keywords
Abstract A unified view of the use of computer vision technology for different types of vehicles

Computer Vision in Vehicle Technology focuses on computer vision as on-board technology, bringing together fields of research where computer vision is progressively penetrating: the automotive sector, unmanned aerial and underwater vehicles. It also serves as a reference for researchers of current developments and challenges in areas of the application of computer vision, involving vehicles such as advanced driver assistance (pedestrian detection, lane departure warning, traffic sign recognition), autonomous driving and robot navigation (with visual simultaneous localization and mapping) or unmanned aerial vehicles (obstacle avoidance, landscape classification and mapping, fire risk assessment).

The overall role of computer vision for the navigation of different vehicles, as well as technology to address on-board applications, is analysed.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-1-118-86807-2 Medium
Area Expedition Conference
Notes DAG Approved no
Call Number Admin @ si @ LIP2017b Serial 3049
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Author Michael Teutsch; Angel Sappa; Riad I. Hammoud
Title Cross-Spectral Image Processing Type Book Chapter
Year 2022 Publication (down) Computer Vision in the Infrared Spectrum. Synthesis Lectures on Computer Vision Abbreviated Journal
Volume Issue Pages 23-34
Keywords
Abstract Although this book is on IR computer vision and its main focus lies on IR image and video processing and analysis, a special attention is dedicated to cross-spectral image processing due to the increasing number of publications and applications in this domain. In these cross-spectral frameworks, IR information is used together with information from other spectral bands to tackle some specific problems by developing more robust solutions. Tasks considered for cross-spectral processing are for instance dehazing, segmentation, vegetation index estimation, or face recognition. This increasing number of applications is motivated by cross- and multi-spectral camera setups available already on the market like for example smartphones, remote sensing multispectral cameras, or multi-spectral cameras for automotive systems or drones. In this chapter, different cross-spectral image processing techniques will be reviewed together with possible applications. Initially, image registration approaches for the cross-spectral case are reviewed: the registration stage is the first image processing task, which is needed to align images acquired by different sensors within the same reference coordinate system. Then, recent cross-spectral image colorization approaches, which are intended to colorize infrared images for different applications are presented. Finally, the cross-spectral image enhancement problem is tackled by including guided super resolution techniques, image dehazing approaches, cross-spectral filtering and edge detection. Figure 3.1 illustrates cross-spectral image processing stages as well as their possible connections. Table 3.1 presents some of the available public cross-spectral datasets generally used as reference data to evaluate cross-spectral image registration, colorization, enhancement, or exploitation results.
Address
Corporate Author Thesis
Publisher Springer Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title SLCV
Series Volume Series Issue Edition
ISSN ISBN 978-3-031-00698-2 Medium
Area Expedition Conference
Notes MSIAU; MACO Approved no
Call Number Admin @ si @ TSH2022b Serial 3805
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Author Michael Teutsch; Angel Sappa; Riad I. Hammoud
Title Detection, Classification, and Tracking Type Book Chapter
Year 2022 Publication (down) Computer Vision in the Infrared Spectrum. Synthesis Lectures on Computer Vision Abbreviated Journal
Volume Issue Pages 35-58
Keywords
Abstract Automatic image and video exploitation or content analysis is a technique to extract higher-level information from a scene such as objects, behavior, (inter-)actions, environment, or even weather conditions. The relevant information is assumed to be contained in the two-dimensional signal provided in an image (width and height in pixels) or the three-dimensional signal provided in a video (width, height, and time). But also intermediate-level information such as object classes [196], locations [197], or motion [198] can help applications to fulfill certain tasks such as intelligent compression [199], video summarization [200], or video retrieval [201]. Usually, videos with their temporal dimension are a richer source of data compared to single images [202] and thus certain video content can be extracted from videos only such as object motion or object behavior. Often, machine learning or nowadays deep learning techniques are utilized to model prior knowledge about object or scene appearance using labeled training samples [203, 204]. After a learning phase, these models are then applied in real world applications, which is called inference.
Address
Corporate Author Thesis
Publisher Springer Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title SLCV
Series Volume Series Issue Edition
ISSN ISBN 978-3-031-00698-2 Medium
Area Expedition Conference
Notes MSIAU; MACO Approved no
Call Number Admin @ si @ TSH2022c Serial 3806
Permanent link to this record
 
 
Author Michael Teutsch; Angel Sappa; Riad I. Hammoud
Title Image and Video Enhancement Type Book Chapter
Year 2022 Publication (down) Computer Vision in the Infrared Spectrum. Synthesis Lectures on Computer Vision Abbreviated Journal
Volume Issue Pages 9-21
Keywords
Abstract Image and video enhancement aims at improving the signal quality relative to imaging artifacts such as noise and blur or atmospheric perturbations such as turbulence and haze. It is usually performed in order to assist humans in analyzing image and video content or simply to present humans visually appealing images and videos. However, image and video enhancement can also be used as a preprocessing technique to ease the task and thus improve the performance of subsequent automatic image content analysis algorithms: preceding dehazing can improve object detection as shown by [23] or explicit turbulence modeling can improve moving object detection as discussed by [24]. But it remains an open question whether image and video enhancement should rather be performed explicitly as a preprocessing step or implicitly for example by feeding affected images directly to a neural network for image content analysis like object detection [25]. Especially for real-time video processing at low latency it can be better to handle image perturbation implicitly in order to minimize the processing time of an algorithm. This can be achieved by making algorithms for image content analysis robust or even invariant to perturbations such as noise or blur. Additionally, mistakes of an individual preprocessing module can obviously affect the quality of the entire processing pipeline.
Address
Corporate Author Thesis
Publisher Springer Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title SLCV
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes MSIAU; MACO Approved no
Call Number Admin @ si @ TSH2022a Serial 3807
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Author Carlo Gatta; Oriol Pujol; Oriol Rodriguez-Leor; J. Mauri; Petia Radeva
Title Improved Rigid Registration of Vessel Structures using the Fast Radial Symmetry Transform Type Conference Article
Year 2008 Publication (down) Computer Vision for Intravascular Imaging CVII’08 Workshop Medical Image Computing and Computer–Assisted Intervention , 11th International Conference Abbreviated Journal
Volume Issue Pages 128–136
Keywords
Abstract
Address NY (USA)
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference MICCAI
Notes MILAB;HUPBA Approved no
Call Number BCNPCL @ bcnpcl @ GPR2008b Serial 1038
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Author Sergio Escalera; Oriol Pujol; J. Mauri; Petia Radeva
Title IVUS Tissue Characterization with Sub-class Error-correcting Output Codes Type Conference Article
Year 2008 Publication (down) Computer Vision and Pattern Recognition Workshops, 2008. CVPR Workshops 2008. IEEE Computer Society Conference on, pp. 1–8, 23–28 juny 2008. Abbreviated Journal
Volume Issue Pages
Keywords
Abstract Intravascular ultrasound (IVUS) represents a powerful imaging technique to explore coronary vessels and to study their morphology and histologic properties. In this paper, we characterize different tissues based on Radio Frequency, texture-based, slope-based, and combined features. To deal with the classification of multiple tissues, we require the use of robust multi-class learning techniques. In this context, we propose a strategy to model multi-class classification tasks using sub-classes information in the ECOC framework. The new strategy splits the classes into different subsets according to the applied base classifier. Complex IVUS data sets containing overlapping data are learnt by splitting the original set of classes into sub-classes, and embedding the binary problems in a problem-dependent ECOC design. The method automatically characterizes different tissues, showing performance improvements over the state-of-the-art ECOC techniques for different base classifiers and feature sets.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference CVPR
Notes MILAB;HuPBA Approved no
Call Number BCNPCL @ bcnpcl @ EPM2008 Serial 1041
Permanent link to this record