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Author Antonio Esteban Lansaque; Carles Sanchez; Agnes Borras; Marta Diez-Ferrer; Antoni Rosell; Debora Gil edit   pdf
openurl 
  Title Stable Airway Center Tracking for Bronchoscopic Navigation Type Conference Article
  Year 2016 Publication 28th Conference of the international Society for Medical Innovation and Technology Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Bronchoscopists use X‐ray fluoroscopy to guide bronchoscopes to the lesion to be biopsied without any kind of incisions. Reducing exposure to X‐ray is important for both patients and doctors but alternatives like electromagnetic navigation require specific equipment and increase the cost of the clinical procedure. We propose a guiding system based on the extraction of airway centers from intra‐operative videos. Such anatomical landmarks could be
matched to the airway centerline extracted from a pre‐planned CT to indicate the best path to the lesion. We present an extraction of lumen centers
from intra‐operative videos based on tracking of maximal stable regions of energy maps.
 
  Address Delft; Rotterdam; Leiden; The Netherlands; October 2016  
  Corporate Author Thesis  
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  Language Summary Language Original Title  
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  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference SMIT  
  Notes IAM; Approved no  
  Call Number (up) Admin @ si @ LSB2016a Serial 2856  
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Author Antonio Esteban Lansaque; Carles Sanchez; Agnes Borras; Marta Diez-Ferrer; Antoni Rosell; Debora Gil edit   pdf
openurl 
  Title Stable Anatomical Structure Tracking for video-bronchoscopy Navigation Type Conference Article
  Year 2016 Publication 19th International Conference on Medical Image Computing and Computer Assisted Intervention Workshops Abbreviated Journal  
  Volume Issue Pages  
  Keywords Lung cancer diagnosis; video-bronchoscopy; airway lumen detection; region tracking  
  Abstract Bronchoscopy allows to examine the patient airways for detection of lesions and sampling of tissues without surgery. A main drawback in lung cancer diagnosis is the diculty to check whether the exploration is following the correct path to the nodule that has to be biopsied. The most extended guidance uses uoroscopy which implies repeated radiation of clinical sta and patients. Alternatives such as virtual bronchoscopy or electromagnetic navigation are very expensive and not completely robust to blood, mocus or deformations as to be extensively used. We propose a method that extracts and tracks stable lumen regions at di erent levels of the bronchial tree. The tracked regions are stored in a tree that encodes the anatomical structure of the scene which can be useful to retrieve the path to the lesion that the clinician should follow to do the biopsy. We present a multi-expert validation of our anatomical landmark extraction in 3 intra-operative ultrathin explorations.  
  Address Athens; Greece; October 2016  
  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 MICCAIW  
  Notes IAM; 600.075 Approved no  
  Call Number (up) Admin @ si @ LSB2016b Serial 2857  
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Author Marta Ligero; Guillermo Torres; Carles Sanchez; Katerine Diaz; Raquel Perez; Debora Gil edit   pdf
url  doi
openurl 
  Title Selection of Radiomics Features based on their Reproducibility Type Conference Article
  Year 2019 Publication 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society Abbreviated Journal  
  Volume Issue Pages 403-408  
  Keywords  
  Abstract Dimensionality reduction is key to alleviate machine learning artifacts in clinical applications with Small Sample Size (SSS) unbalanced datasets. Existing methods rely on either the probabilistic distribution of training data or the discriminant power of the reduced space, disregarding the impact of repeatability and uncertainty in features.In the present study is proposed the use of reproducibility of radiomics features to select features with high inter-class correlation coefficient (ICC). The reproducibility includes the variability introduced in the image acquisition, like medical scans acquisition parameters and convolution kernels, that affects intensity-based features and tumor annotations made by physicians, that influences morphological descriptors of the lesion.For the reproducibility of radiomics features three studies were conducted on cases collected at Vall Hebron Oncology Institute (VHIO) on responders to oncology treatment. The studies focused on the variability due to the convolution kernel, image acquisition parameters, and the inter-observer lesion identification. The features selected were those features with a ICC higher than 0.7 in the three studies.The selected features based on reproducibility were evaluated for lesion malignancy classification using a different database. Results show better performance compared to several state-of-the-art methods including Principal Component Analysis (PCA), Kernel Discriminant Analysis via QR decomposition (KDAQR), LASSO, and an own built Convolutional Neural Network.  
  Address Berlin; Alemanya; July 2019  
  Corporate Author Thesis  
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  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
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  ISSN ISBN Medium  
  Area Expedition Conference EMBC  
  Notes IAM; 600.139; 600.145 Approved no  
  Call Number (up) Admin @ si @ LTS2019 Serial 3358  
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Author Patricia Marquez edit  isbn
openurl 
  Title A Confidence Framework for the Assessment of Optical Flow Performance Type Book Whole
  Year 2015 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Optical Flow (OF) is the input of a wide range of decision support systems such as car driver assistance, UAV guiding or medical diagnose. In these real situations, the absence of ground truth forces to assess OF quality using quantities computed from either sequences or the computed optical flow itself. These quantities are generally known as Confidence Measures, CM. Even if we have a proper confidence measure we still need a way to evaluate its ability to discard pixels with an OF prone to have a large error. Current approaches only provide a descriptive evaluation of the CM performance but such approaches are not capable to fairly compare different confidence measures and optical flow algorithms. Thus, it is of prime importance to define a framework and a general road map for the evaluation of optical flow performance.

This thesis provides a framework able to decide which pairs “ optical flow – confidence measure” (OF-CM) are best suited for optical flow error bounding given a confidence level determined by a decision support system. To design this framework we cover the following points:

Descriptive scores. As a first step, we summarize and analyze the sources of inaccuracies in the output of optical flow algorithms. Second, we present several descriptive plots that visually assess CM capabilities for OF error bounding. In addition to the descriptive plots, given a plot representing OF-CM capabilities to bound the error, we provide a numeric score that categorizes the plot according to its decreasing profile, that is, a score assessing CM performance.
Statistical framework. We provide a comparison framework that assesses the best suited OF-CM pair for error bounding that uses a two stage cascade process. First of all we assess the predictive value of the confidence measures by means of a descriptive plot. Then, for a sample of descriptive plots computed over training frames, we obtain a generic curve that will be used for sequences with no ground truth. As a second step, we evaluate the obtained general curve and its capabilities to really reflect the predictive value of a confidence measure using the variability across train frames by means of ANOVA.

The presented framework has shown its potential in the application on clinical decision support systems. In particular, we have analyzed the impact of the different image artifacts such as noise and decay to the output of optical flow in a cardiac diagnose system and we have improved the navigation inside the bronchial tree on bronchoscopy.
 
  Address July 2015  
  Corporate Author Thesis Ph.D. thesis  
  Publisher Ediciones Graficas Rey Place of Publication Editor Debora Gil;Aura Hernandez  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-84-943427-2-1 Medium  
  Area Expedition Conference  
  Notes IAM; 600.075 Approved no  
  Call Number (up) Admin @ si @ Mar2015 Serial 2687  
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Author H. Martin ; Jens Fagertun; Sergio Vera; Debora Gil edit   pdf
openurl 
  Title Medial structure generation for registration of anatomical structures Type Book Chapter
  Year 2017 Publication Skeletonization, Theory, Methods and Applications Abbreviated Journal  
  Volume 11 Issue Pages  
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  Area Expedition Conference  
  Notes IAM; 600.096; 600.075; 600.145 Approved no  
  Call Number (up) Admin @ si @ MFV2017a Serial 2935  
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Author H.Martin Kjer; Jens Fagertuna; Sergio Vera; Debora Gil; Miguel Angel Gonzalez Ballester; Rasmus R. Paulsena edit   pdf
url  openurl
  Title Free-form image registration of human cochlear uCT data using skeleton similarity as anatomical prior Type Journal Article
  Year 2016 Publication Patter Recognition Letters Abbreviated Journal PRL  
  Volume 76 Issue 1 Pages 76-82  
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  Area Expedition Conference  
  Notes IAM; 600.060 Approved no  
  Call Number (up) Admin @ si @ MFV2017b Serial 2941  
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Author Enric Marti; Antoni Gurgui; Debora Gil; Aura Hernandez-Sabate; Jaume Rocarias; Ferran Poveda edit   pdf
openurl 
  Title ABP on line: Seguimiento, estregas y evaluación en aprendizaje basado en proyectos Type Miscellaneous
  Year 2014 Publication 8th International Congress on University Teaching and Innovation Abbreviated Journal  
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  Address Tarragona; juliol 2014  
  Corporate Author Thesis  
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  Area Expedition Conference CIDUI  
  Notes IAM; ADAS; 600.076; 600.063; 600.075 Approved no  
  Call Number (up) Admin @ si @ MGG2014 Serial 2457  
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Author Patricia Marquez; Debora Gil; Aura Hernandez-Sabate edit   pdf
url  doi
openurl 
  Title Evaluation of the Capabilities of Confidence Measures for Assessing Optical Flow Quality Type Conference Article
  Year 2013 Publication ICCV Workshop on Computer Vision in Vehicle Technology: From Earth to Mars Abbreviated Journal  
  Volume Issue Pages 624-631  
  Keywords  
  Abstract Assessing Optical Flow (OF) quality is essential for its further use in reliable decision support systems. The absence of ground truth in such situations leads to the computation of OF Confidence Measures (CM) obtained from either input or output data. A fair comparison across the capabilities of the different CM for bounding OF error is required in order to choose the best OF-CM pair for discarding points where OF computation is not reliable. This paper presents a statistical probabilistic framework for assessing the quality of a given CM. Our quality measure is given in terms of the percentage of pixels whose OF error bound can not be determined by CM values. We also provide statistical tools for the computation of CM values that ensures a given accuracy of the flow field.  
  Address Sydney; Australia; December 2013  
  Corporate Author Thesis  
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  ISSN ISBN Medium  
  Area Expedition Conference CVTT:E2M  
  Notes IAM; ADAS; 600.044; 600.057; 601.145 Approved no  
  Call Number (up) Admin @ si @ MGH2013b Serial 2351  
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Author Patricia Marquez; Debora Gil; R.Mester; Aura Hernandez-Sabate edit   pdf
openurl 
  Title Local Analysis of Confidence Measures for Optical Flow Quality Evaluation Type Conference Article
  Year 2014 Publication 9th International Conference on Computer Vision Theory and Applications Abbreviated Journal  
  Volume 3 Issue Pages 450-457  
  Keywords Optical Flow; Confidence Measure; Performance Evaluation.  
  Abstract Optical Flow (OF) techniques facing the complexity of real sequences have been developed in the last years. Even using the most appropriate technique for our specific problem, at some points the output flow might fail to achieve the minimum error required for the system. Confidence measures computed from either input data or OF output should discard those points where OF is not accurate enough for its further use. It follows that evaluating the capabilities of a confidence measure for bounding OF error is as important as the definition
itself. In this paper we analyze different confidence measures and point out their advantages and limitations for their use in real world settings. We also explore the agreement with current tools for their evaluation of confidence measures performance.
 
  Address Lisboa; January 2014  
  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 VISAPP  
  Notes IAM; ADAS; 600.044; 600.060; 600.057; 601.145; 600.076; 600.075 Approved no  
  Call Number (up) Admin @ si @ MGM2014 Serial 2432  
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Author Saad Minhas; Aura Hernandez-Sabate; Shoaib Ehsan; Klaus McDonald Maier edit  doi
openurl 
  Title Effects of Non-Driving Related Tasks during Self-Driving mode Type Journal Article
  Year 2022 Publication IEEE Transactions on Intelligent Transportation Systems Abbreviated Journal TITS  
  Volume 23 Issue 2 Pages 1391-1399  
  Keywords  
  Abstract Perception reaction time and mental workload have proven to be crucial in manual driving. Moreover, in highly automated cars, where most of the research is focusing on Level 4 Autonomous driving, take-over performance is also a key factor when taking road safety into account. This study aims to investigate how the immersion in non-driving related tasks affects the take-over performance of drivers in given scenarios. The paper also highlights the use of virtual simulators to gather efficient data that can be crucial in easing the transition between manual and autonomous driving scenarios. The use of Computer Aided Simulations is of absolute importance in this day and age since the automotive industry is rapidly moving towards Autonomous technology. An experiment comprising of 40 subjects was performed to examine the reaction times of driver and the influence of other variables in the success of take-over performance in highly automated driving under different circumstances within a highway virtual environment. The results reflect the relationship between reaction times under different scenarios that the drivers might face under the circumstances stated above as well as the importance of variables such as velocity in the success on regaining car control after automated driving. The implications of the results acquired are important for understanding the criteria needed for designing Human Machine Interfaces specifically aimed towards automated driving conditions. Understanding the need to keep drivers in the loop during automation, whilst allowing drivers to safely engage in other non-driving related tasks is an important research area which can be aided by the proposed study.  
  Address Feb. 2022  
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  Area Expedition Conference  
  Notes IAM; 600.139; 600.145 Approved no  
  Call Number (up) Admin @ si @ MHE2022 Serial 3468  
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