international_conferences-peer_reviewed_articles.bib
@inproceedings{AliAbbood2017EA-LNCS,
booktitle = {Biennial International Conference on Artificial Evolution (EA-2017)},
editor = {\'E. Lutton and P. Legrand and P. Parrend and N. Monmarch\'e and M. Schoenauer},
title = {Basic, Dual, Adaptive, and Directed Mutation Operators in the {Fly} Algorithm},
author = {Zainab Ali Abbood and Franck P. Vidal},
year = {2018},
volume = {????},
series = {Lecture Notes in Computer Science},
pages = {???-???},
publisher = {Springer, Heidelberg},
isbn = {???},
month = {???},
doi = {????},
address = {Paris, France},
abstract = {Our work is based on a Cooperative Co-evolution Algorithm -- the Fly algorithm --
in which individuals correspond to 3-D points. The Fly algorithm uses two levels of fitness
function: i) a local fitness computed to evaluate a given individual (usually during
the selection process) and ii) a global fitness to assess the performance of the population
as a whole. This global fitness is the metrics that is minimised (or maximised depending on
the problem) by the optimiser. Here the solution of the optimisation problem corresponds
to a set of individuals instead of a single individual (the best individual) as in
classical evolutionary algorithms. The Fly algorithm heavily relies on mutation operators
and a new blood operator to insure diversity in the population. To lead to accurate results,
a large mutation variance is often initially used to avoid local minima (or maxima). It is
then progressively reduced to refine the results. Another approach is the use of adaptive
operators. However, very little research on adaptive operators in Fly algorithm has been
conducted. We address this deficiency and propose 4 different fully adaptive mutation
operators in the Fly algorithm: positrons, and the final solution of the algorithm
approximates the radioactivity concentration. The view and analysis four mutation operators,
which are Basic Mutation, Adaptive Mutation Variance, Dual Mutation, and Directed Mutation.
Due to the complex nature of the search space, ($kN$-dimensions, with $k$ the number of
genes per individuals and $N$ the number of individuals in the population),
we favour operators with a low maintenance cost in terms of computations.
Their impact on the algorithm efficiency is analysed and validated on positron emission
tomography (PET) reconstruction.},
keywords = {evolutionary algorithms, Parisian approach, reconstruction algorithms, positron emission tomography, mutation operator},
pdf = {pdf/AliAbbood2017EA-LNCS.pdf}
}
@inproceedings{AliAbbood2017EA1,
booktitle = {Biennial International Conference on Artificial Evolution (EA-2017)},
editor = {\'E. Lutton and P. Legrand and P. Parrend and N. Monmarch\'e and M. Schoenauer},
title = {Basic, Dual, Adaptive, and Directed Mutation Operators in the {Fly} Algorithm},
author = {Zainab Ali Abbood and Franck P. Vidal},
year = {2017},
pages = {106-119},
isbn = {978-2-9539267-7-4},
month = oct,
address = {Paris, France},
annotation = {Oct~25--27, 2017},
abstract = {Our work is based on a Cooperative Co-evolution Algorithm -- the Fly algorithm --
in which individuals correspond to 3-D points. The Fly algorithm uses two levels of fitness
function: i) a local fitness computed to evaluate a given individual (usually during
the selection process) and ii) a global fitness to assess the performance of the population
as a whole. This global fitness is the metrics that is minimised (or maximised depending on
the problem) by the optimiser. Here the solution of the optimisation problem corresponds
to a set of individuals instead of a single individual (the best individual) as in
classical evolutionary algorithms. The Fly algorithm heavily relies on mutation operators
and a new blood operator to insure diversity in the population. To lead to accurate results,
a large mutation variance is often initially used to avoid local minima (or maxima). It is
then progressively reduced to refine the results. Another approach is the use of adaptive
operators. However, very little research on adaptive operators in Fly algorithm has been
conducted. We address this deficiency and propose 4 different fully adaptive mutation
operators in the Fly algorithm: positrons, and the final solution of the algorithm
approximates the radioactivity concentration. The view and analysis four mutation operators,
which are Basic Mutation, Adaptive Mutation Variance, Dual Mutation, and Directed Mutation.
Due to the complex nature of the search space, ($kN$-dimensions, with $k$ the number of
genes per individuals and $N$ the number of individuals in the population),
we favour operators with a low maintenance cost in terms of computations.
Their impact on the algorithm efficiency is analysed and validated on positron emission
tomography (PET) reconstruction.},
keywords = {evolutionary algorithms, Parisian approach, reconstruction algorithms, positron emission tomography, mutation operator},
pdf = {pdf/AliAbbood2017EA1.pdf}
}
@inproceedings{AliAbbood2017EA2,
booktitle = {Biennial International Conference on Artificial Evolution (EA-2017)},
editor = {\'E. Lutton and P. Legrand and P. Parrend and N. Monmarch\'e and M. Schoenauer},
title = {Fly4Arts: Evolutionary Digital Art with the Fly Algorithm},
author = {Zainab Ali Abbood and Franck P. Vidal},
year = {2017},
pages = {313},
isbn = {978-2-9539267-7-4},
month = oct,
address = {Paris, France},
annotation = {Oct~25--27, 2017},
abstract = {The aim of this study is to generate artistic images, such as digital mosaics, as an optimisation
problem without the introduction of any a priori knowledge or constraint other than an input image. The usual
practice to produce digital mosaic images heavily relies on Centroidal Voronoi diagrams. We demonstrate here
that it can be modelled as an optimisation problem solved using a cooperative co-evolution strategy based on the
Parisian evolution approach, the Fly algorithm. An individual is called a fly. Its aim of the algorithm is to optimise
the position of innitely small 3-D points (the flies). The Fly algorithm has been initially used in real-time stereo
vision for robotics. It has also demonstrated promising results in image reconstruction for tomography. In this
new application, a much more complex representation has been studied. A fly is a tile. It has its own position,
size, colour, and rotation angle. Our method takes advantage of graphics processing units (GPUs) to generate
the images using the modern OpenGL Shading Language (GLSL) and Open Computing Language (OpenCL) to
compute the difference between the input image and simulated image. Different types of tiles are implemented,
some with transparency, to generate different visual effects, such as digital mosaic and spray paint. An online study
with 41 participants has been conducted to compare some of our results with those generated using an open-source
software for image manipulation. It demonstrates that our method leads to more visually appealing images.},
keywords = {Digital mosaic, Evolutionary art, Fly algorithm, Parisian evolution, cooperative co-evolution},
pdf = {pdf/AliAbbood2017EA2.pdf}
}
@inproceedings{Abbood2017EvoIASP,
author = {Z. {Ali Abbood} and O. Amlal and F. P. Vidal},
title = {Evolutionary Art Using the Fly Algorithm},
booktitle = {Applications of Evolutionary Computation},
year = 2017,
series = {Lecture Notes in Computer Science},
volume = 10199,
pages = {455-470},
month = apr,
address = {Amsterdam, The Netherlands},
annotation = {Apr~19--21, 2017},
abstract = {This study is about Evolutionary art such as digital mosaics.
The most common techniques to generate a digital mosaic effect heavily
rely on Centroidal Voronoi diagrams. Our method generates artistic images
as an optimisation problem without the introduction of any a priori
knowledge or constraint other than the input image. We adapt
a cooperative co-evolution strategy based on the Parisian evolution
approach, the Fly algorithm, to produce artistic visual effects from
an input image (e.g. a photograph). The primary usage of the Fly algorithm
is in computer vision, especially stereo-vision in robotics. It has also
been used in image reconstruction for tomography. Until now the individuals
correspond to simplistic primitives: Infinitely small 3-D points. In this
paper, the individuals have a much more complex representation and
represent tiles in a mosaic. They have their own position, size, colour,
and rotation angle. We take advantage of graphics processing units (GPUs)
to generate the images using the modern OpenGL Shading Language. Different
types of tiles are implemented, some with transparency, to generate
different visual effects, such as digital mosaic and spray paint. A user
study has been conducted to evaluate some of our results. We also compare
results with those obtained with GIMP, an open-source software for image
manipulation.},
doi = {10.1007/978-3-319-55849-3_30},
publisher = {Springer, Heidelberg},
keywords = {Digital mosaic, Evolutionary art, Fly algorithm,
Parisian evolution, Cooperative co-evolution},
pdf = {pdf/Abbood2017EvoIASP.pdf},
}
@inproceedings{RIVIC-EG2013,
author = {N. W. John and M. Jones and R. Martin and
F. P. Vidal and R. Zwiggelaar},
title = {The Research Institute of Visual Computing, {RIVIC}},
booktitle = {Eurographics 2013 Lab Presentation},
year = 2013,
month = may,
editor = {J. C. Torres and A. L\'ecuyer},
address = {Girona, Spain},
annotation = {May~6--10, 2013},
abstract = {Visual computing represents one of the most challenging and
inspiring arenas in computer science. Today, fifty percent of content on
the internet is in the form of visual data and information, and more than
fifty percent of the neurons in the human brain are used in visual
perception and reasoning. RIVIC is the collaborative amalgamation of
research programmes between the computer science departments in
Aberystwyth, Bangor, Cardiff and Swansea universities. Its aim is
to promote research in visual computing, e.g.~visualisation, computer
vision and image/video processing, computer graphics and
virtual environments.},
doi = {10.2312/conf/EG2013/lab/L08},
ISSN = {1017-4656},
publisher = {Eurographics Association},
pdf = {pdf/RIVIC-EG2013.pdf}
}
@inproceedings{Vidal2013MIBISOC-A,
author = {F. P. Vidal and Y. L. Pavia and {J.-M.} Rocchisani and J. Louchet and
\'E. Lutton},
title = {Artificial Evolution Strategy for PET Reconstruction},
booktitle = {International Conference on Medical Imaging Using Bio-Inspired and
Soft Computing (MIBISOC2013)},
year = 2013,
month = may,
address = {Brussels, Belgium},
annotation = {May~15--17, 2013},
pages = {39-46},
abstract = {This paper shows new resutls of our artificial evolution algorithm
for Positron Emission Tomography (PET) reconstruction. This imaging technique
produces datasets corresponding to the concentration of positron emitters
within the patient. Fully three-dimensional (3D) tomographic reconstruction
requires high computing power and leads to many challenges. Our aim is
to produce high quality datasets in a time that is clinically acceptable.
Our method is based on a co-evolution strategy called the ``Fly algorithm''.
Each fly represents a point in space and mimics a positron emitter. Each fly
position is progressively optimised using evolutionary computing to closely
match the data measured by the imaging system. The performance of
each fly is assessed based on its positive or negative contribution to
the performance of the whole population. The final population of flies
approximates the radioactivity concentration. This approach has shown
promising results on numerical phantom models. The size of objects and
their relative concentrations can be calculated in two-dimensional (2D)
space. In (3D), complex shapes can be reconstructed. In this paper,
we demonstrate the ability of the algorithm to fidely reconstruct more
anatomically realistic volumes.},
keywords = {Evolutionary computation, inverse problems, adaptive algorithm, Nuclear medicine, Positron emission tomography, Reconstruction algorithms},
pdf = {pdf/Vidal2013MIBISOC-A.pdf}
}
@inproceedings{Vidal2013MIBISOC-B,
author = {\textbf{F. P. Vidal} and {P.-F.} Villard and \'E. Lutton},
title = {Automatic tuning of respiratory model for patient-based simulation},
booktitle = {International Conference on Medical Imaging Using Bio-Inspired and
Soft Computing (MIBISOC2013)},
year = 2013,
month = may,
address = {Brussels, Belgium},
annotation = {May~15--17, 2013},
pages = {225-231},
abstract = {This paper is an overview of a method recently published
in a biomedical journal (IEEE Transactions on Biomedical
Engineering, http://tbme.embs.org). The method is based
on an optimisation technique
called ``evolutionary strategy'' and it has been designed to
estimate the parameters of a complex 15-D respiration model.
This model is adaptable to account for patient's specificities.
The aim of the optimisation algorithm is to finely tune the
model so that it accurately fits real patient datasets. The final
results can then be embedded, for example, in high fidelity
simulations of the human physiology. Our algorithm is fully
automatic and adaptive. A compound fitness function has been
designed to take into account for various quantities that have
to be minimised (here topological errors of the liver and the
diaphragm geometries). The performance our implementation is
compared with two traditional methods (downhill simplex and
conjugate gradient descent), a random search and a basic real-valued
genetic algorithm. It shows that our evolutionary scheme
provides results that are significantly more stable and accurate
than the other tested methods. The approach is relatively generic
and can be easily adapted to other complex parametrisation
problems when ground truth data is available.},
keywords = {Evolutionary computation, inverse problems, medical simulation, adaptive algorithm},
pdf = {pdf/Vidal2013MIBISOC-B.pdf}
}
@inproceedings{Villard2012MMVR,
author = {{P.-F.} Villard and F. P. Vidal and F. Bello and N. W. John},
title = {A Method to Compute Respiration Parameters for Patient-based Simulators},
booktitle = {Proceeding of Medicine Meets Virtual Reality 19 - NextMed (MMVR19)},
year = 2012,
series = {Studies in Health Technology and Informatics},
volume = 173,
pages = {529-533},
month = feb,
address = {Newport Beach, California},
annotation = {Feb~9--11, 2012},
note = {Winner of the best poster award},
abstract = {We propose a method to automatically tune a patient-based virtual environment training
simulator for abdominal needle insertion. The key attributes to be customized in our framework are
the elasticity of soft-tissues and the respiratory model parameters. The estimation is based on two
3D Computed Tomography (CT) scans of the same patient at two different time steps. Results are
presented on five patients and show that our new method leads to better results than our previous
studies with manually tuned parameters.},
pmid = {22357051},
publisher = {IOS Press},
pdf = {pdf/Villard2012MMVR.pdf}
}
@inproceedings{Vidal2010PPSN,
author = {F. P. Vidal and \'E. Lutton and J. Louchet and {J.-M.} Rocchisani},
title = {Threshold selection, mitosis and dual mutation in cooperative coevolution:
application to medical {3D} tomography},
booktitle = {International Conference on Parallel Problem Solving From Nature
(PPSN'10)},
year = 2010,
series = {Lecture Notes in Computer Science},
volume = 6238,
pages = {414-423},
month = sep,
address = {Krakow, Poland},
annotation = {Sept~11--15, 2010},
abstract = {We present and analyse the behaviour of specialised operators
designed for cooperative coevolution strategy in the framework of
3D tomographic PET reconstruction. The basis is a simple cooperative
co-evolution scheme (the ``fly algorithm''), which embeds the searched
solution in the whole population, letting each individual be only a part
of the solution. An individual, or fly, is a 3D point that emits positrons.
Using a cooperative co-evolution scheme to optimize the position of
positrons, the population of flies evolves so that the data estimated from
flies matches measured data. The final population approximates the radioactivity
concentration. In this paper, three operators are proposed,
threshold selection, mitosis and dual mutation, and their impact on the
algorithm efficiency is experimentally analysed on a controlled test-case.
Their extension to other cooperative co-evolution schemes is discussed.},
doi = {10.1007/978-3-642-15844-5_42},
publisher = {Springer, Heidelberg},
pdf = {pdf/Vidal2010PPSN.pdf}
}
@inproceedings{Vidal2010EGPoster,
author = {F. P. Vidal and M. Garnier and N. Freud and J. M. L\'etang and N. W. John},
title = {Accelerated Deterministic Simulation of X-ray Attenuation Using Graphics Hardware},
booktitle = {Eurographics 2010 - Poster},
year = 2010,
pages = {Poster 5011},
month = may,
address = {Norrk"{o}ping, Sweden},
annotation = {May~3--7, 2010},
abstract = {In this paper, we propose a deterministic simulation of X-ray transmission imaging on graphics hardware. Only
the directly transmitted photons are simulated, using the Beer-Lambert law. Our previous attempt to simulate Xray
attenuation from polygon meshes utilising the GPU showed significant increase of performance, with respect
to a validated software implementation, without loss of accuracy. However, the simulations were restricted to
monochromatic X-rays and finite point sources. We present here an extension to our method to perform physically
more realistic simulations by taking into account polychromatic X-rays and focal spots causing blur.},
keywords = {Three-Dimensional Graphics and Realism; Raytracing; Physical Sciences and Engineering; Physics},
publisher = {Eurographics Association},
pdf = {pdf/Vidal2010EGPoster.pdf}
}
@inproceedings{Vidal2010EvoIASP,
author = {F. P. Vidal and J. Louchet and {J.-M.} Rocchisani and \'E. Lutton},
title = {New genetic operators in the {Fly} algorithm: application to medical
{PET} image reconstruction},
booktitle = {Applications of Evolutionary Computation},
year = 2010,
series = {Lecture Notes in Computer Science},
volume = 6024,
pages = {292-301},
month = apr,
address = {Istanbul, Turkey},
annotation = {Apr~7--9, 2010},
note = {Nominated for best paper award},
abstract = {This paper presents an evolutionary approach for image reconstruction
in positron emission tomography (PET). Our reconstruction
method is based on a cooperative coevolution strategy (also called
Parisian evolution): the ``fly algorithm''. Each fly is a 3D point that
mimics a positron emitter. The flies' position is progressively optimised
using evolutionary computing to closely match the data measured by
the imaging system. The performance of each fly is assessed using a
``marginal evaluation'' based on the positive or negative contribution of
this fly to the performance of the population. Using this property, we
propose a ``thresholded-selection'' method to replace the classical tournament
method. A mitosis operator is also proposed. It is triggered to
automatically increase the population size when the number of flies with
negative fitness becomes too low.},
doi = {10.1007/978-3-642-12239-2_30},
publisher = {Springer, Heidelberg},
pdf = {pdf/Vidal2010EvoIASP.pdf}
}
@inproceedings{Vidal2009EA,
author = {F. P. Vidal and D. {Lazaro-Ponthus} and S. Legoupil and
J. Louchet and \'E. Lutton and {J.-M.} Rocchisani},
title = {Artificial Evolution for {3D} {PET} Reconstruction},
booktitle = {Proceedings of the 9th international conference on Artificial Evolution (EA'09)},
year = 2009,
series = {Lecture Notes in Computer Science},
volume = 5975,
pages = {37-48},
month = oct,
address = {Strasbourg, France},
annotation = {OCt~26--28, 2009},
abstract = {This paper presents a method to take advantage of artificial
evolution in positron emission tomography reconstruction. This imaging
technique produces datasets that correspond to the concentration of
positron emitters through the patient. Fully 3D tomographic reconstruction
requires high computing power and leads to many challenges. Our
aim is to reduce the computing cost and produce datasets while retaining
the required quality. Our method is based on a coevolution strategy (also
called Parisian evolution) named ``Fly algorithm''. Each fly represents a
point of the space and acts as a positron emitter. The final population of
flies corresponds to the reconstructed data. Using ``marginal evaluation'',
the fly's fitness is the positive or negative contribution of this fly to the
performance of the population. This is also used to skip the relatively
costly step of selection and simplify the evolutionary algorithm.},
doi = {10.1007/978-3-642-14156-0_4},
publisher = {Springer, Heidelberg},
pdf = {pdf/Vidal2009EA.pdf}
}
@inproceedings{Bello2009EGMedPrize,
author = {F. Bello and A. Bulpitt and D. A. Gould and R. Holbrey and C. Hunt and
N. W. John and S. Johnson and R. Phillips and A. Sinha and F. P. Vidal and
{P.-F.} Villard and H. Woolnough},
title = {{ImaGiNe-S}: Imaging Guided Needle Simulation},
booktitle = {Eurographics 2009 - Medical Prize},
year = 2009,
pages = {5-8},
month = mar,
address = {Munich, Germany},
annotation = {Mar~30--Apr~3, 2009},
note = {Second prize and winner of \texteuro 300},
abstract = {We present an integrated system for training visceral needle puncture
procedures. Our aim is to provide a cost effective and validated
training tool that uses actual patient data to enable interventional
radiology trainees to learn how to carry out image-guided needle
puncture. The input data required is a computed tomography scan of
the patient that is used to create the patient specific models. Force
measurements have been made on real tissue and the resulting data
is incorporated into the simulator. Respiration and soft tissue deformations
are also carried out to further improve the fidelity of the simulator.},
keywords = {Physically based modelling, Virtual reality},
doi = {10.2312/egm.20091024},
publisher = {Eurographics Association},
pdf = {pdf/Imagines.pdf}
}
@inproceedings{Vidal2009MMVR,
author = {F. P. Vidal and {P.-F.} Villard and R. Holbrey and N. W. John and
F. Bello and A. Bulpitt and D. A. Gould},
title = {Developing An Immersive Ultrasound Guided Needle Puncture Simulator},
booktitle = {Proceeding of Medicine Meets Virtual Reality 17 (MMVR17)},
year = 2009,
series = {Studies in Health Technology and Informatics},
volume = 142,
pages = {398-400},
month = jan,
address = {Long Beach, California},
annotation = {Jan~19--22, 2012},
abstract = {We present an integrated system for training ultrasound guided
needle puncture. Our aim is to provide a cost effective and validated
training tool that uses actual patient data to enable interventional
radiology trainees to learn how to carry out image-guided needle
puncture. The input data required is a computed tomography scan of
the patient that is used to create the patient specific models. Force
measurements have been made on real tissue and the resulting data is
incorporated into the simulator. Respiration and soft tissue
deformations are also carried out to further improve the fidelity of
the simulator.},
keywords = {image guided needle puncture training, interventional radiology
training, needle puncture},
pmid = {19377193},
publisher = {IOS Press},
pdf = {pdf/Vidal2009MMVR.pdf}
}
@inproceedings{apCynydd2009MMVR,
author = {L. {ap Cynydd} and N. W. John and F. P. Vidal and D. A. Gould and
E. Joekes and P. Littler},
title = {Cost Effective Ultrasound Imaging Training Mentor for use in Developing Countries},
booktitle = {Proceeding of Medicine Meets Virtual Reality 17 (MMVR17)},
year = 2009,
series = {Studies in Health Technology and Informatics},
volume = 142,
pages = {49-54},
month = jan,
address = {Long Beach, California},
annotation = {Jan~19--22, 2012},
abstract = {This paper reports on a low cost system for training ultrasound imaging
techniques. The need for such training is particularly acute in developing
countries where typically ultrasound scanners remain idle due to
the lack of experienced sonographers. The system described below
is aimed at a PC platform but uses interface components from the
Nintendo Wii games console. The training software is being designed
to support a variety of patient case studies, and also supports remote
tutoring over the internet.},
keywords = {Ultrasound Training, medical virtual environment, hci},
pmid = {19377112},
publisher = {IOS Press},
pdf = {pdf/John2009MMVR.pdf}
}
@inproceedings{John2008MMVR,
author = {N. W. John and V. Luboz and F. Bello and C. Hughes and F. P. Vidal and
I. S. Lim and T. V. How and J. Zhai and S. Johnson and N. Chalmers and
K. Brodlie and A. Bulpit and Y. Song and D. O. Kessel and R. Phillips and
J. W. Ward and S. Pisharody and Y. Zhang and C. M. Crawshaw and D. A. Gould},
title = {Physics-based virtual environment for training core skills in vascular
interventional radiological procedures},
booktitle = {Proceeding of Medicine Meets Virtual Reality 16 (MMVR16)},
year = 2008,
series = {Studies in Health Technology and Informatics},
volume = 132,
pages = {195-197},
month = jan,
address = {Long Beach, California},
annotation = {Jan~29--Feb~1, 2008},
abstract = {Recent years have seen a significant increase in the use of Interventional
Radiology (IR) as an alternative to open surgery. A large number
of IR procedures commences with needle puncture of a vessel to insert
guidewires and catheters: these clinical skills are acquired by all
radiologists during training on patients, associated with some discomfort
and occasionally, complications. While some visual skills can be
acquired using models such as the ones used in surgery, these have
limitations for IR which relies heavily on a sense of touch. Both
patients and trainees would benefit from a virtual environment (VE)
conveying touch sensation to realistically mimic procedures. The
authors are developing a high fidelity VE providing a validated alternative
to the traditional apprenticeship model used for teaching the core
skills. The current version of the CRaIVE simulator combines home
made software, haptic devices and commercial equipments.},
keywords = {Virtual environment, patient specific model, interventional radiology},
pmid = {18391285},
publisher = {IOS Press}
}
@inproceedings{Vidal2007MMVR,
author = {F. P. Vidal and N. W. John and R.M. Guillemot},
title = {Interactive Physically-based {X-ray} simulation: {CPU} or {GPU}?},
booktitle = {Proceeding of Medicine Meets Virtual Reality 15 (MMVR15)},
year = 2007,
series = {Studies in Health Technology and Informatics},
volume = 125,
pages = {479-481},
month = feb,
address = {Long Beach, California},
annotation = {Feb~6--9, 2007},
abstract = {Interventional Radiology (IR) procedures are minimally invasive, targeted
treatments performed using imaging for guidance. Needle puncture
using ultrasound, x-ray, or computed tomography (CT) images is a
core task in the radiology curriculum, and we are currently devel-
oping a training simulator for this. One requirement is to include
support for physically-based simulation of x-ray images from CT data
sets. In this paper, we demonstrate how to exploit the capability
of today's graphics cards to efficiently achieve this on the Graphics
Processing Unit (GPU) and compare performance with an efficient software
only implementation using the Central Processing Unit (CPU).},
keywords = {X-ray simulation, GPU-based volume rendering, Interventional radiology},
pmid = {17377331},
publisher = {IOS Press}
}
@inproceedings{Vidal2005CARS,
author = {F. P. Vidal and N. Chalmers and D. A. Gould and A. E. Healey and N. W. John},
title = {Developing a needle guidance virtual environment with patient specific data and force feedback},
booktitle = {Proceeding of the 19th International Congress of Computer Assisted Radiology and Surgery (CARS'05)},
year = 2005,
series = {International Congress Series},
volume = 1281,
pages = {418-423},
month = jun,
address = {Berlin, Germany},
annotation = {Jun~22--25, 2005},
abstract = {We present a simulator for guided needle puncture procedures. Our
aim is to provide an effective training tool for students in interventional
radiology (IR) using actual patient data and force feedback within
an immersive virtual environment (VE). Training of the visual and
motor skills required in IR is an apprenticeship which still consists
of close supervision using the model: (i) see one, (ii) do one, and
(iii) teach one. Training in patients not only has discomfort associated
with it, but provides limited access to training scenarios, and makes
it difficult to train in a time efficient manner. Currently, the
majority of commercial products implementing a medical VE still focus
on laparoscopy where eye-hand coordination and sensation are key
issues. IR procedures, however, are far more reliant on the sense
of touch. Needle guidance using ultrasound or computed tomography
(CT) images is also widely used. Both of these are areas that have
not been fully addressed by other medical VEs. This paper provides
details of how we are developing an effective needle guidance simulator.
The project is a multi-disciplinary collaboration involving practising
interventional radiologists and computer scientists.},
keywords = {Interventional radiology; Virtual environments; Needle puncture; Haptics},
doi = {10.1016/j.ics.2005.03.200},
publisher = {Elsevier},
pdf = {pdf/Vidal2005CARS.pdf}
}
@inproceedings{Vidal2004EGSTAR,
author = {F. P. Vidal and F. Bello and K. Brodlie and N. W. John and
D. Gould and R. Phillips and N. Avis},
title = {Principles and Applications of Medical Virtual Environments},
booktitle = {State-of-the-art Proceedings of Eurographics 2004},
year = 2004,
pages = {1-35},
month = aug,
address = {Grenoble, France},
annotation = {Aug~30--Sept~3, 2004},
abstract = {The medical domain offers many excellent opportunities for the application
of computer graphics, visualization, and virtual environments, offering
the potential to help improve healthcare and bring benefits to patients.
This report provides a comprehensive overview of the state-of-the-art
in this exciting field. It has been written from the perspective
of both computer scientists and practicing clinicians and documents
past and current successes together with the challenges that lie
ahead. The report begins with a description of the commonly used
imaging modalities and then details the software algorithms and hardware
that allows visualization of and interaction with this data. Example
applications from research projects and commercially available products
are listed, including educational tools; diagnostic aids; virtual
endoscopy; planning aids; guidance aids; skills training; computer
augmented reality; and robotics. The final section of the report
summarises the current issues and looks ahead to future developments.},
keywords = {Augmented and virtual realities, Computer Graphics, Health, Physically based modelling, Medical Sciences, Simulation, Virtual device interfaces},
editor = {Christophe Schlick and Werner Purgathofer},
issn = {1017-4656},
doi = {10.2312/egst.20041024},
publisher = {Eurographics Association},
pdf = {pdf/Vidal2004EGSTAR.pdf}
}
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