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A. M. Here, B. C. Lopez, Debora Gil, J. J. Camarero, & Jordi Martinez-Vilalta. (2013). "A new software to analyse wood anatomical features in conifer species " In International Symposium on Wood Structure in Plant Biology and Ecology.
Abstract: International Symposium on Wood Structure in Plant Biology and Ecology
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Sergio Vera, Miguel Angel Gonzalez Ballester, & Debora Gil. (2013). "Volumetric Anatomical Parameterization and Meshing for Inter-patient Liver Coordinate System Deffinition " In 16th International Conference on Medical Image Computing and Computer Assisted Intervention.
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Ferran Poveda, Debora Gil, & Enric Marti. (2012). "Multi-resolution DT-MRI cardiac tractography " In Statistical Atlases And Computational Models Of The Heart: Imaging and Modelling Challenges (Vol. 7746, pp. 270–277). Springer Berlin Heidelberg.
Abstract: Even using objective measures from DT-MRI no consensus about myocardial architecture has been achieved so far. Streamlining provides good reconstructions at low level of detail, but falls short to give global abstract interpretations. In this paper, we present a multi-resolution methodology that is able to produce simplified representations of cardiac architecture. Our approach produces a reduced set of tracts that are representative of the main geometric features of myocardial anatomical structure. Experiments show that fiber geometry is preserved along reductions, which validates the simplified model for interpretation of cardiac architecture.
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Debora Gil, Agnes Borras, Ruth Aris, Mariano Vazquez, Pierre Lafortune, & Guillame Houzeaux. (2012). "What a difference in biomechanics cardiac fiber makes " In Statistical Atlases And Computational Models Of The Heart: Imaging and Modelling Challenges (Vol. 7746, pp. 253–260). Springer Berlin Heidelberg.
Abstract: Computational simulations of the heart are a powerful tool for a comprehensive understanding of cardiac function and its intrinsic relationship with its muscular architecture. Cardiac biomechanical models require a vector field representing the orientation of cardiac fibers. A wrong orientation of the fibers can lead to a
non-realistic simulation of the heart functionality. In this paper we explore the impact of the fiber information on the simulated biomechanics of cardiac muscular anatomy. We have used the John Hopkins database to perform a biomechanical simulation using both a synthetic benchmark fiber distribution and the data obtained experimentally from DTI. Results illustrate how differences in fiber orientation affect heart deformation along cardiac cycle.
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Sergio Vera, Miguel Angel Gonzalez Ballester, & Debora Gil. (2012). "A medial map capturing the essential geometry of organs " In ISBI Workshop on Open Source Medical Image Analysis software (1691 - 1694). IEEE.
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
Keywords: Medial Surface Representation, Volume Reconstruction,Geometry , Image reconstruction , Liver , Manifolds , Shape , Surface morphology , Surface reconstruction
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Guillermo Torres, Jan Rodríguez Dueñas, Sonia Baeza, Antoni Rosell, Carles Sanchez, & Debora Gil. (2023). "Prediction of Malignancy in Lung Cancer using several strategies for the fusion of Multi-Channel Pyradiomics Images " In 7th Workshop on Digital Image Processing for Medical and Automotive Industry in the framework of SYNASC 2023.
Abstract: 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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Guillermo Torres, Debora Gil, Antoni Rosell, S. Mena, & Carles Sanchez. (2023)." Virtual Radiomics Biopsy for the Histological Diagnosis of Pulmonary Nodules" In 37th International Congress and Exhibition is organized by Computer Assisted Radiology and Surgery.
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Sonia Baeza, Debora Gil, Carles Sanchez, Guillermo Torres, Ignasi Garcia Olive, Ignasi Guasch, et al. (2023)." Biopsia virtual radiomica para el diagnóstico histológico de nódulos pulmonares – Resultados intermedios del proyecto Radiolung" In SEPAR.
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Debora Gil, Guillermo Torres, & Carles Sanchez. (2023)." Transforming radiomic features into radiological words" In IEEE International Symposium on Biomedical Imaging.
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Pau Cano, Debora Gil, & Eva Musulen. (2023)." Towards automatic detection of helicobacter pylori in histological samples of gastric tissue" In IEEE International Symposium on Biomedical Imaging.
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