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Jaume Garcia; Francesc Carreras; Sandra Pujades; Debora Gil |
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Regional motion patterns for the Left Ventricle function assessment |
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2008 |
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Proc. 19th Int. Conf. Pattern Recognition ICPR 2008 |
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1-4 |
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Regional scores (e.g. strain, perfusion) of the Left Ventricle (LV) functionality are playing an increasing role in the diagnosis of cardiac diseases. A main limitation is the lack of normality models for complementary scores oriented to assessment of the LV integrity. This paper introduces an original framework based on a parametrization of the LV domain, which allows comparison across subjects of local physiological measures of different nature. We compute regional normality patterns in a feature space characterizing the LV function. We show the consistency of the model for the regional motion on healthy and hypokinetic pathological cases |
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IAM @ iam @ GCP2008 |
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1510 |
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Aura Hernandez-Sabate; Debora Gil; Josefina Mauri; Petia Radeva |
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Title |
Reducing cardiac motion in IVUS sequences |
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2006 |
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Proceeding of Computers in Cardiology |
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33 |
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685-688 |
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Cardiac vessel displacement is a main artifact in IVUS sequences. It hinders visualization of the main structures in an appropriate orientation and alignment and affects extracting vessel measurements. In this paper, we present a novel approach for image sequence alignment based on spectral analysis, which removes rigid dynamics, preserving at the same time the vessel geometry. First, we suppress the translation by taking, for each frame, the center of mass of the image as origin of coordinates. In polar coordinates with such point as origin, the rotation appears as a horizontal displacement. The translation induces a phase shift in the Fourier coefficients of two consecutive polar images. We estimate the phase by adjusting a regression plane to the phases of the principal frequencies. Experiments show that the presented strategy suppress cardiac motion regardless of the acquisition device. 1. |
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IAM; MILAB |
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IAM @ iam @ HGM2006a |
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1554 |
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Oriol Rodriguez-Leor; Josefina Mauri; Eduard Fernandez-Nofrerias; C. Garcia; R. Villuendas; Vicente del Valle; Debora Gil; Petia Radeva |
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Reconstruction of a spatio-temporal model of the intima layer from intravascular ultrasound sequences |
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2003 |
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European Heart Journal |
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ESC Congress |
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IAM;MILAB |
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IAM @ iam @ RMF2003c |
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1641 |
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M. Gomez; Josefina Mauri; Eduard Fernandez-Nofrerias; Oriol Rodriguez-Leor; Carme Julia; Debora Gil; Petia Radeva |
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Reconstrucción de un modelo espacio-temporal de la luz del vaso a partir de secuencias de ecografía intracoronaria |
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2002 |
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XXXVIII Congreso Nacional de la Sociedad Española de Cardiología. |
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IAM;ADAS;MILAB |
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IAM @ iam @ GMF2002d |
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1516 |
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Aura Hernandez-Sabate; Jose Elias Yauri; Pau Folch; Miquel Angel Piera; Debora Gil |
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Title |
Recognition of the Mental Workloads of Pilots in the Cockpit Using EEG Signals |
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2022 |
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Applied Sciences |
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APPLSCI |
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12 |
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5 |
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2298 |
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Cognitive states; Mental workload; EEG analysis; Neural networks; Multimodal data fusion |
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The commercial flightdeck is a naturally multi-tasking work environment, one in which interruptions are frequent come in various forms, contributing in many cases to aviation incident reports. Automatic characterization of pilots’ workloads is essential to preventing these kind of incidents. In addition, minimizing the physiological sensor network as much as possible remains both a challenge and a requirement. Electroencephalogram (EEG) signals have shown high correlations with specific cognitive and mental states, such as workload. However, there is not enough evidence in the literature to validate how well models generalize in cases of new subjects performing tasks with workloads similar to the ones included during the model’s training. In this paper, we propose a convolutional neural network to classify EEG features across different mental workloads in a continuous performance task test that partly measures working memory and working memory capacity. Our model is valid at the general population level and it is able to transfer task learning to pilot mental workload recognition in a simulated operational environment. |
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February 2022 |
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IAM; ADAS; 600.139; 600.145; 600.118 |
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Admin @ si @ HYF2022 |
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3720 |
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Antoni Rosell; Sonia Baeza; S. Garcia-Reina; JL. Mate; Ignasi Guasch; I. Nogueira; I. Garcia-Olive; Guillermo Torres; Carles Sanchez; Debora Gil |
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Radiomics to increase the effectiveness of lung cancer screening programs. Radiolung preliminary results. |
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2022 |
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European Respiratory Journal |
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ERJ |
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60 |
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66 |
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Admin @ si @ RBG2022c |
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3835 |
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Carles Sanchez; Debora Gil; R. Tazi; Jorge Bernal; Y. Ruiz; L. Planas; F. Javier Sanchez; Antoni Rosell |
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Quasi-real time digital assessment of Central Airway Obstruction |
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2015 |
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3rd European congress for bronchology and interventional pulmonology ECBIP2015 |
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Barcelona; Spain; April 2015 |
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ECBIP |
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IAM; MV; 600.075 |
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SGT2015 |
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2612 |
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Hanne Kause; Patricia Marquez; Andrea Fuster; Aura Hernandez-Sabate; Luc Florack; Debora Gil; Hans van Assen |
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Quality Assessment of Optical Flow in Tagging MRI |
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2015 |
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5th Dutch Bio-Medical Engineering Conference BME2015 |
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The Netherlands; January 2015 |
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BME |
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IAM; ADAS; 600.076; 600.075 |
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Admin @ si @ KMF2015 |
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2616 |
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Guillermo Torres; Jan Rodríguez Dueñas; Sonia Baeza; Antoni Rosell; Carles Sanchez; Debora Gil |
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Prediction of Malignancy in Lung Cancer using several strategies for the fusion of Multi-Channel Pyradiomics Images |
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2023 |
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7th Workshop on Digital Image Processing for Medical and Automotive Industry in the framework of SYNASC 2023 |
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This study shows the generation process and the subsequent study of the representation space obtained by extracting GLCM texture features from computer-aided tomography (CT) scans of pulmonary nodules (PN). For this, data from 92 patients from the Germans Trias i Pujol University Hospital were used. The workflow focuses on feature extraction using Pyradiomics and the VGG16 Convolutional Neural Network (CNN). The aim of the study is to assess whether the data obtained have a positive impact on the diagnosis of lung cancer (LC). To design a machine learning (ML) model training method that allows generalization, we train SVM and neural network (NN) models, evaluating diagnosis performance using metrics defined at slice and nodule level. |
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DIPMAI |
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Admin @ si @ TRB2023 |
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3926 |
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Marta Diez-Ferrer; Debora Gil; Elena Carreño; Susana Padrones; Samantha Aso |
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Positive Airway Pressure-Enhanced CT to Improve Virtual Bronchoscopic Navigation |
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2017 |
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Journal of Thoracic Oncology |
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JTO |
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12 |
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1S |
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S596-S597 |
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Thorax CT; diagnosis; Peripheral Pulmonary Nodule |
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A main weakness of virtual bronchoscopic navigation (VBN) is unsuccessful segmentation of distal branches approaching peripheral pulmonary nodules (PPN). CT scan acquisition protocol is pivotal for segmentation covering the utmost periphery. We hypothesize that application of continuous positive airway pressure (CPAP) during CT acquisition could improve visualization and segmentation of peripheral bronchi. The purpose of the present pilot study is to compare quality of segmentations under 4 CT acquisition modes: inspiration (INSP), expiration (EXP) and both with CPAP (INSP-CPAP and EXP-CPAP). |
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IAM; 600.096; 600.075; 600.145 |
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Admin @ si @ DGC2017a |
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2883 |
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