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Author Debora Gil; Guillermo Torres edit   pdf
openurl 
  Title A multi-shape loss function with adaptive class balancing for the segmentation of lung structures Type Conference Article
  Year 2020 Publication 34th International Congress and Exhibition on Computer Assisted Radiology & Surgery Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Virtual; June 2020  
  Corporate Author Thesis  
  Publisher (up) 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 CARS  
  Notes IAM; 600.139; 600.145 Approved no  
  Call Number Admin @ si @ GiT2020 Serial 3472  
Permanent link to this record
 

 
Author Debora Gil; Oriol Ramos Terrades; Raquel Perez edit   pdf
openurl 
  Title Topological Radiomics (TOPiomics): Early Detection of Genetic Abnormalities in Cancer Treatment Evolution Type Conference Article
  Year 2020 Publication Women in Geometry and Topology Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Barcelona; September 2019  
  Corporate Author Thesis  
  Publisher (up) 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 IAM; DAG; 600.139; 600.145; 600.121 Approved no  
  Call Number Admin @ si @ GRP2020 Serial 3473  
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Author Esmitt Ramirez; Carles Sanchez; Debora Gil edit   pdf
url  doi
openurl 
  Title Localizing Pulmonary Lesions Using Fuzzy Deep Learning Type Conference Article
  Year 2019 Publication 21st International Symposium on Symbolic and Numeric Algorithms for Scientific Computing Abbreviated Journal  
  Volume Issue Pages 290-294  
  Keywords  
  Abstract The usage of medical images is part of the clinical daily in several healthcare centers around the world. Particularly, Computer Tomography (CT) images are an important key in the early detection of suspicious lung lesions. The CT image exploration allows the detection of lung lesions before any invasive procedure (e.g. bronchoscopy, biopsy). The effective localization of lesions is performed using different image processing and computer vision techniques. Lately, the usage of deep learning models into medical imaging from detection to prediction shown that is a powerful tool for Computer-aided software. In this paper, we present an approach to localize pulmonary lung lesion using fuzzy deep learning. Our approach uses a simple convolutional neural network based using the LIDC-IDRI dataset. Each image is divided into patches associated a probability vector (fuzzy) according their belonging to anatomical structures on a CT. We showcase our approach as part of a full CAD system to exploration, planning, guiding and detection of pulmonary lesions.  
  Address Timisoara; Rumania; September 2019  
  Corporate Author Thesis  
  Publisher (up) 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 SYNASC  
  Notes IAM; 600.145; 600.140; 601.337; 601.323 Approved no  
  Call Number Admin @ si @ RSG2019 Serial 3531  
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Author Jose Yauri; Aura Hernandez-Sabate; Pau Folch; Debora Gil edit  doi
openurl 
  Title Mental Workload Detection Based on EEG Analysis Type Conference Article
  Year 2021 Publication Artificial Intelligent Research and Development. Proceedings 23rd International Conference of the Catalan Association for Artificial Intelligence. Abbreviated Journal  
  Volume 339 Issue Pages 268-277  
  Keywords Cognitive states; Mental workload; EEG analysis; Neural Networks.  
  Abstract The study of mental workload becomes essential for human work efficiency, health conditions and to avoid accidents, since workload compromises both performance and awareness. Although workload has been widely studied using several physiological measures, minimising the sensor network as much as possible remains both a challenge and a requirement.
Electroencephalogram (EEG) signals have shown a high correlation to specific cognitive and mental states like workload. However, there is not enough evidence in the literature to validate how well models generalize in case of new subjects performing tasks of a workload similar to the ones included during model’s training.
In this paper we propose a binary neural network to classify EEG features across different mental workloads. Two workloads, low and medium, are induced using two variants of the N-Back Test. The proposed model was validated in a dataset collected from 16 subjects and shown a high level of generalization capability: model reported an average recall of 81.81% in a leave-one-out subject evaluation.
 
  Address Virtual; October 20-22 2021  
  Corporate Author Thesis  
  Publisher (up) 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 CCIA  
  Notes IAM; 600.139; 600.118; 600.145 Approved no  
  Call Number Admin @ si @ Serial 3723  
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Author Josep Llados; Ernest Valveny; Gemma Sanchez; Enric Marti edit  url
isbn  openurl
  Title A Case Study of Pattern Recognition: Symbol Recognition in Graphic Documentsa Type Conference Article
  Year 2003 Publication Proceedings of Pattern Recognition in Information Systems Abbreviated Journal  
  Volume Issue Pages 1-13  
  Keywords  
  Abstract  
  Address Angers, France  
  Corporate Author Thesis  
  Publisher (up) ICEIS Press Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 972-98816-3-4 Medium  
  Area Expedition Conference PRIS'03  
  Notes DAG;IAM; Approved no  
  Call Number IAM @ iam @ LVS2003 Serial 1576  
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Author Aura Hernandez-Sabate; Monica Mitiko; Sergio Shiguemi; Debora Gil edit   pdf
url  isbn
openurl 
  Title A validation protocol for assessing cardiac phase retrieval in IntraVascular UltraSound Type Conference Article
  Year 2010 Publication Computing in Cardiology Abbreviated Journal  
  Volume 37 Issue Pages 899-902  
  Keywords  
  Abstract A good reliable approach to cardiac triggering is of utmost importance in obtaining accurate quantitative results of atherosclerotic plaque burden from the analysis of IntraVascular UltraSound. Although, in the last years, there has been an increase in research of methods for retrospective gating, there is no general consensus in a validation protocol. Many methods are based on quality assessment of longitudinal cuts appearance and those reporting quantitative numbers do not follow a standard protocol. Such heterogeneity in validation protocols makes faithful comparison across methods a difficult task. We propose a validation protocol based on the variability of the retrieved cardiac phase and explore the capability of several quality measures for quantifying such variability. An ideal detector, suitable for its application in clinical practice, should produce stable phases. That is, it should always sample the same cardiac cycle fraction. In this context, one should measure the variability (variance) of a candidate sampling with respect a ground truth (reference) sampling, since the variance would indicate how spread we are aiming a target. In order to quantify the deviation between the sampling and the ground truth, we have considered two quality scores reported in the literature: signed distance to the closest reference sample and distance to the right of each reference sample. We have also considered the residuals of the regression line of reference against candidate sampling. The performance of the measures has been explored on a set of synthetic samplings covering different cardiac cycle fractions and variabilities. From our simulations, we conclude that the metrics related to distances are sensitive to the shift considered while the residuals are robust against fraction and variabilities as far as one can establish a pair-wise correspondence between candidate and reference. We will further investigate the impact of false positive and negative detections in experimental data.  
  Address  
  Corporate Author Thesis  
  Publisher (up) IEEE Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0276-6547 ISBN 978-1-4244-7318-2 Medium  
  Area Expedition Conference CINC  
  Notes IAM; Approved no  
  Call Number IAM @ iam @ HSM2010 Serial 1551  
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Author Patricia Marquez; Debora Gil; Aura Hernandez-Sabate edit   pdf
url  doi
openurl 
  Title A Confidence Measure for Assessing Optical Flow Accuracy in the Absence of Ground Truth Type Conference Article
  Year 2011 Publication IEEE International Conference on Computer Vision – Workshops Abbreviated Journal  
  Volume Issue Pages 2042-2049  
  Keywords IEEE International Conference on Computer Vision – Workshops  
  Abstract Optical flow is a valuable tool for motion analysis in autonomous navigation systems. A reliable application requires determining the accuracy of the computed optical flow. This is a main challenge given the absence of ground truth in real world sequences. This paper introduces a measure of optical flow accuracy for Lucas-Kanade based flows in terms of the numerical stability of the data-term. We call this measure optical flow condition number. A statistical analysis over ground-truth data show a good statistical correlation between the condition number and optical flow error. Experiments on driving sequences illustrate its potential for autonomous navigation systems.  
  Address  
  Corporate Author Thesis  
  Publisher (up) IEEE Place of Publication Barcelona (Spain) Editor  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ICCVW  
  Notes IAM; ADAS Approved no  
  Call Number IAM @ iam @ MGH2011 Serial 1682  
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Author Albert Andaluz; Francesc Carreras; Cristina Santa Marta;Debora Gil edit   pdf
url  openurl
  Title Myocardial torsion estimation with Tagged-MRI in the OsiriX platform Type Conference Article
  Year 2012 Publication ISBI Workshop on Open Source Medical Image Analysis software Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Myocardial torsion (MT) plays a crucial role in the assessment of the functionality of the
left ventricle. For this purpose, the IAM group at the CVC has developed the Harmonic Phase Flow (HPF) plugin for the Osirix DICOM platform . We have validated its funcionalty on sequences acquired using different protocols and including healthy and pathological cases. Results show similar torsion trends for SPAMM acquisitions, with pathological cases introducing expected deviations from the ground truth. Finally, we provide the plugin free of charge at http://iam.cvc.uab.es
 
  Address Barcelona, Spain  
  Corporate Author Thesis  
  Publisher (up) IEEE Place of Publication Editor Wiro Niessen (Erasmus MC) and Marc Modat (UCL)  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ISBI  
  Notes IAM Approved no  
  Call Number IAM @ iam @ ACS2012 Serial 1900  
Permanent link to this record
 

 
Author Sergio Vera; Miguel Angel Gonzalez Ballester; Debora Gil edit   pdf
doi  isbn
openurl 
  Title A medial map capturing the essential geometry of organs Type Conference Article
  Year 2012 Publication ISBI Workshop on Open Source Medical Image Analysis software Abbreviated Journal  
  Volume Issue Pages 1691 - 1694  
  Keywords Medial Surface Representation, Volume Reconstruction,Geometry , Image reconstruction , Liver , Manifolds , Shape , Surface morphology , Surface reconstruction  
  Abstract Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Accurate computation of one pixel wide medial surfaces is mandatory. Those surfaces must represent faithfully the geometry of the volume. Although morphological methods produce excellent results in 2D, their complexity and quality drops across dimensions, due to a more complex description of pixel neighborhoods. This paper introduces a continuous operator for accurate and efficient computation of medial structures of arbitrary dimension. Our experiments show its higher performance for medical imaging applications in terms of simplicity of medial structures and capability for reconstructing the anatomical volume  
  Address Barcelona,Spain  
  Corporate Author Thesis  
  Publisher (up) IEEE Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1945-7928 ISBN 978-1-4577-1857-1 Medium  
  Area Expedition Conference ISBI  
  Notes IAM Approved no  
  Call Number IAM @ iam @ VGG2012a Serial 1989  
Permanent link to this record
 

 
Author Petia Radeva; A.Amini; J.Huang; Enric Marti edit   pdf
url  doi
isbn  openurl
  Title Deformable B-Solids and Implicit Snakes for Localization and Tracking of SPAMM MRI-Data Type Conference Article
  Year 1996 Publication Workshop on Mathematical Methods in Biomedical Image Analysis Abbreviated Journal  
  Volume Issue Pages 192-201  
  Keywords  
  Abstract To date, MRI-SPAMM data from different image slices have been analyzed independently. In this paper, we propose an approach for 3D tag localization and tracking of SPAMM data by a novel deformable B-solid. The solid is defined in terms of a 3D tensor product B-spline. The isoparametric curves of the B-spline solid have special importance. These are termed implicit snakes as they deform under image forces from tag lines in different image slices. The localization and tracking of tag lines is performed under constraints of continuity and smoothness of the B-solid. The framework unifies the problems of localization, and displacement fitting and interpolation into the same procedure utilizing B-spline bases for interpolation. To track motion from boundaries and restrict image forces to the myocardium, a volumetric model is employed as a pair of coupled endocardial and epicardial B-spline surfaces. To recover deformations in the LV an energy-minimization problem is posed where both tag and ...  
  Address San Francisco CA  
  Corporate Author Thesis  
  Publisher (up) IEEE Computer Society Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 0-8186-7368-0 Medium  
  Area Expedition Conference MMBIA ’96  
  Notes MILAB;IAM; Approved no  
  Call Number IAM @ iam @ RAH1996 Serial 1630  
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