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Author |
Sergio Vera; Miguel Angel Gonzalez Ballester; Debora Gil |
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Title |
Volumetric Anatomical Parameterization and Meshing for Inter-patient Liver Coordinate System Deffinition |
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Conference Article |
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2013 |
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16th International Conference on Medical Image Computing and Computer Assisted Intervention |
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Nagoya; Japan; September 2013 |
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MICCAI |
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no |
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Admin @ si @ VGG2013 |
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2301 |
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Author |
Ferran Poveda; Enric Marti; Debora Gil; Francesc Carreras; Manel Ballester |
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Title |
Helical Structure of Ventricular Anatomy by Diffusion Tensor Cardiac MR Tractography |
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Journal Article |
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Year |
2012 |
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Journal of American College of Cardiology |
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JACC |
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Volume |
5 |
Issue |
7 |
Pages |
754-755 |
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It is widely accepted that myocardial fiber architecture plays a critical role in myocardial contractility and relaxation (1). However, there is a lack of consensus about the distribution of the myocardial fibers and their spatial arrangement in the left and right ventricles. An understanding of the cardiac architecture should benefit the ventricular functional assessment, left ventricular reconstructive surgery planning, or resynchronization therapy in heart failure. Researchers have proposed several conceptual models to describe the architecture of the heart, ranging from gross dissection to histological presentation. The cardiac mesh model (2) proposes that the myocytes are arranged longitudinally and radially change their angulation along the myocardial depth. By contrast, the helical ventricular myocardial model states that the ventricular myocardium is a continuous anatomical helical layout of myocardial fibers (1 |
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1936-878X |
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IAM @ iam @ PMG2012 |
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1985 |
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Author |
Ferran Poveda; Debora Gil;Enric Marti |
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Title |
Multi-resolution DT-MRI cardiac tractography |
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Conference Article |
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Year |
2012 |
Publication |
Statistical Atlases And Computational Models Of The Heart: Imaging and Modelling Challenges |
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7746 |
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270-277 |
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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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Nice, France |
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Springer Berlin Heidelberg |
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LNCS |
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0302-9743 |
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978-3-642-36960-5 |
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STACOM |
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IAM @ iam @ PGM2012 |
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1986 |
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Author |
Debora Gil;Agnes Borras;Ruth Aris;Mariano Vazquez;Pierre Lafortune; Guillame Houzeaux |
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Title |
What a difference in biomechanics cardiac fiber makes |
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Conference Article |
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2012 |
Publication |
Statistical Atlases And Computational Models Of The Heart: Imaging and Modelling Challenges |
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7746 |
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253-260 |
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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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Nice, France |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-36960-5 |
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STACOM |
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IAM @ iam @ GBA2012 |
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1987 |
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Author |
Sergio Vera; Miguel Angel Gonzalez Ballester; Debora Gil |
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Title |
Optimal Medial Surface Generation for Anatomical Volume Representations |
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Book Chapter |
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2012 |
Publication |
Abdominal Imaging. Computational and Clinical Applications |
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LNCS |
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7601 |
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265-273 |
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Medial surface representation; volume reconstruction |
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Medial representations are a widely used technique in abdominal organ shape representation and parametrization. Those methods require good medial manifolds as a starting point. Any medial
surface used to parametrize a volume should be simple enough to allow an easy manipulation and complete enough to allow an accurate reconstruction of the volume. Obtaining good quality medial
surfaces is still a problem with current iterative thinning methods. This forces the usage of generic, pre-calculated medial templates that are adapted to the final shape at the cost of a drop in volume reconstruction.
This paper describes an operator for generation of medial structures that generates clean and complete manifolds well suited for their further use in medial representations of abdominal organ volumes. While being simpler than thinning surfaces, experiments show its high performance in volume reconstruction and preservation of medial surface main branching topology. |
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Nice, France |
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Springer Berlin Heidelberg |
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Yoshida, Hiroyuki and Hawkes, David and Vannier, MichaelW. |
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Lecture Notes in Computer Science |
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0302-9743 |
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978-3-642-33611-9 |
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STACOM |
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IAM |
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IAM @ iam @ VGG2012b |
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1988 |
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Author |
Sergio Vera; Miguel Angel Gonzalez Ballester; Debora Gil |
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Title |
A medial map capturing the essential geometry of organs |
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Conference Article |
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Year |
2012 |
Publication |
ISBI Workshop on Open Source Medical Image Analysis software |
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1691 - 1694 |
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Medial Surface Representation, Volume Reconstruction,Geometry , Image reconstruction , Liver , Manifolds , Shape , Surface morphology , Surface reconstruction |
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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 |
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Barcelona,Spain |
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IEEE |
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1945-7928 |
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978-1-4577-1857-1 |
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ISBI |
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IAM |
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IAM @ iam @ VGG2012a |
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1989 |
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Author |
Marta Diez-Ferrer; Debora Gil; Elena Carreño; Susana Padrones; Samantha Aso; Vanesa Vicens; Noelia Cubero de Frutos; Rosa Lopez Lisbona; Carles Sanchez; Agnes Borras; Antoni Rosell |
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Title |
Positive Airway Pressure-Enhanced CT to Improve Virtual Bronchoscopic Navigation |
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Journal Article |
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2017 |
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European Respiratory Journal |
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ERJ |
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Admin @ si @ DGC2017b |
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3632 |
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Author |
Pau Cano; Alvaro Caravaca; Debora Gil; Eva Musulen |
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Title |
Diagnosis of Helicobacter pylori using AutoEncoders for the Detection of Anomalous Staining Patterns in Immunohistochemistry Images |
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Miscellaneous |
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2023 |
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Arxiv |
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107241 |
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This work addresses the detection of Helicobacter pylori a bacterium classified since 1994 as class 1 carcinogen to humans. By its highest specificity and sensitivity, the preferred diagnosis technique is the analysis of histological images with immunohistochemical staining, a process in which certain stained antibodies bind to antigens of the biological element of interest. This analysis is a time demanding task, which is currently done by an expert pathologist that visually inspects the digitized samples.
We propose to use autoencoders to learn latent patterns of healthy tissue and detect H. pylori as an anomaly in image staining. Unlike existing classification approaches, an autoencoder is able to learn patterns in an unsupervised manner (without the need of image annotations) with high performance. In particular, our model has an overall 91% of accuracy with 86\% sensitivity, 96% specificity and 0.97 AUC in the detection of H. pylori. |
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Admin @ si @ CCG2023 |
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3855 |
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Author |
Guillermo Torres; Debora Gil |
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A multi-shape loss function with adaptive class balancing for the segmentation of lung structures |
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Journal Article |
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2020 |
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International Journal of Computer Assisted Radiology and Surgery |
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IJCAR |
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15 |
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1 |
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S154-55 |
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Admin @ si @ ToG2020 |
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3590 |
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Author |
Aura Hernandez-Sabate; Jose Elias Yauri; Pau Folch; Daniel Alvarez; Debora Gil |
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Title |
EEG Dataset Collection for Mental Workload Predictions in Flight-Deck Environment |
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Journal Article |
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2024 |
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Sensors |
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SENS |
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24 |
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4 |
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1174 |
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High mental workload reduces human performance and the ability to correctly carry out complex tasks. In particular, aircraft pilots enduring high mental workloads are at high risk of failure, even with catastrophic outcomes. Despite progress, there is still a lack of knowledge about the interrelationship between mental workload and brain functionality, and there is still limited data on flight-deck scenarios. Although recent emerging deep-learning (DL) methods using physiological data have presented new ways to find new physiological markers to detect and assess cognitive states, they demand large amounts of properly annotated datasets to achieve good performance. We present a new dataset of electroencephalogram (EEG) recordings specifically collected for the recognition of different levels of mental workload. The data were recorded from three experiments, where participants were induced to different levels of workload through tasks of increasing cognition demand. The first involved playing the N-back test, which combines memory recall with arithmetical skills. The second was playing Heat-the-Chair, a serious game specifically designed to emphasize and monitor subjects under controlled concurrent tasks. The third was flying in an Airbus320 simulator and solving several critical situations. The design of the dataset has been validated on three different levels: (1) correlation of the theoretical difficulty of each scenario to the self-perceived difficulty and performance of subjects; (2) significant difference in EEG temporal patterns across the theoretical difficulties and (3) usefulness for the training and evaluation of AI models. |
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Admin @ si @ HYF2024 |
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4019 |
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