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% This file was created with JabRef 2.10.
% Encoding: Cp1252
@Misc{3Dircadb2013,
Title = {3D Image Reconstruction for Comparison of Algorithm Database},
Author = {3Dircadb},
HowPublished = {http://www.ircad.fr/softwares/3Dircadb/3Dircadb.php},
Month = jun,
Year = {2013}
}
@InProceedings{Allard2007,
Title = {SOFA an Open Source Framework for Medical Simulation},
Author = {J. Allard and S. Cotin and F. Faure and P.-J. Bensoussan and F. Poyer and C. Duriez and H. Delingette and L. Grisoni B},
Booktitle = {In Medicine Meets Virtual Reality (MMVR 15)},
Year = {2007}
}
@InCollection{Allard2011,
Title = {{Implicit FEM Solver on GPU for Interactive Deformation Simulation}},
Author = {Allard, J{\'e}r{\'e}mie and Courtecuisse, Hadrien and Faure, Fran{\c c}ois},
Booktitle = {{GPU Computing Gems Jade Edition}},
Publisher = {Elsevier},
Year = {2011},
Editor = {Wen-mei W. Hwu },
Month = Nov,
Pages = {281-294},
Abstract = {{We present a set of methods to implement an implicit Finite Element solver on the GPU. In contrast to previous FEM implementations on the GPU which only address explicit time integration, our method allows large time steps for arbitrarily stiff objects. Unlike previous GPU-based sparse solvers, we avoid the assembly of the system matrix, and parallelize the matrix op- erations directly on the original object mesh. This considerably reduces the number of operations required, and more importantly the consumed band- width, enabling the method to be fast enough for highly complex interactive stiff body simulations. The presented methods can be applied in game and visual effects simulations, as well as medical and physics applications, where FEM is well established but currently limited by its computational cost. The core of the method can also be applied to many other scientific appli- cations where a large irregular sparse system of equations is solved using an iterative method.}},
Affiliation = {SHACRA - INRIA Lille - Nord Europe / INRIA Nancy - Grand Est / LIFL , EVASION - INRIA Grenoble Rh{\^o}ne-Alpes / LJK Laboratoire Jean Kuntzmann , IMAGINE - Inria Grenoble Rh{\^o}ne-Alpes / LJK Laboratoire Jean Kuntzmann},
Audience = {international },
Doi = {10.1016/B978-0-12-385963-1.00021-6 },
Hal_id = {inria-00589200},
ISBN = {9780123859631 },
Language = {English},
Url = {http://hal.inria.fr/inria-00589200}
}
@Article{Alterovitz2009,
Title = {{Sensorless Motion Planning for Medical Needle Insertion in Deformable Tissues}},
Author = {Alterovitz, R. and Goldberg, K.Y. and Pouliot, J. and Hsu, IC},
Journal = {IEEE Transactions on Information Technology in Biomedicine},
Year = {2009},
Number = {2},
Pages = {217--225},
Volume = {13},
Abstract = {Minimally invasive medical procedures such as
biopsies, anesthesia drug injections, and brachytherapy cancer
treatments require inserting a needle to a specific target inside
soft tissues. This is difficult because needle insertion displaces
and deforms the surrounding soft tissues causing the target
to move during the procedure. To facilitate physician training
and preoperative planning for these procedures, we develop a
needle insertion motion planning system based on an interactive
simulation of needle insertion in deformable tissues and
numerical optimization to reduce placement error. We describe
a 2-D physically based, dynamic simulation of needle insertion
that uses a finite-element model of deformable soft tissues and
models needle cutting and frictional forces along the needle shaft.
The simulation offers guarantees on simulation stability for mesh
modifications and achieves interactive, real-time performance on
a standard PC. Using texture mapping, the simulation provides
visualization comparable to ultrasound images that the physician
would see during the procedure. We use the simulation as a
component of a sensorless planning algorithm that uses numerical
optimization to compute needle insertion offsets that compensate
for tissue deformations. We apply the method to radioactive seed
implantation during permanent seed prostate brachytherapy to
minimize seed placement error.},
File = {:D\:\\StefanIAIM\\Dokumente\\Literatur\\JabRef\\Image-Guided Surgery\\Sensorless Motion Planning for Medical Needle Insertion in Deformable Tissues.pdf:PDF}
}
@Article{Alterovitz2006,
Title = {{Registration of MR prostate images with biomechanical modeling and nonlinear parameter estimation}},
Author = {Alterovitz, R. and Goldberg, K. and Pouliot, J. and Hsu, I.C.J. and Kim, Y. and Noworolski, S.M. and Kurhanewicz, J.},
Journal = {Medical Physics},
Year = {2006},
Pages = {446},
Volume = {33},
Abstract = {Magnetic resonance imaging MRI and magnetic resonance spectroscopic imaging MRSI have
been shown to be very useful for identifying prostate cancers. For high sensitivity, the MRI/MRSI
examination is often acquired with an endorectal probe that may cause a substantial deformation of
the prostate and surrounding soft tissues. Such a probe is removed prior to radiation therapy
treatment. To register diagnostic probe-in magnetic resonance MR images to therapeutic probeout
MR images for treatment planning, a new deformable image registration method is developed
based on biomechanical modeling of soft tissues and estimation of uncertain tissue parameters
using nonlinear optimization. Given two-dimensional 2-D segmented probe-in and probe-out
images, a finite element method FEM is used to estimate the deformation of the prostate and
surrounding tissues due to displacements and forces resulting from the endorectal probe. Since
FEM requires tissue stiffness properties and external force values as input, the method estimates
uncertain parameters using nonlinear local optimization. The registration method is evaluated using
images from five balloon and five rigid endorectal probe patient cases. It requires on average 37 s
of computation time on a 1.6 GHz Pentium-M PC. Comparing the prostate outline in deformed
probe-out images to corresponding probe-in images, the method obtains a mean Dice Similarity
Coefficient DSC of 97.5% for the balloon probe cases and 98.1% for the rigid probe cases. The
method improves significantly over previous methods P0.05 with greater improvement for
balloon probe cases with larger tissue deformations.},
File = {:D\:\\StefanIAIM\\Dokumente\\Literatur\\JabRef\\Image-Guided Surgery\\Registration of MR prostate images with biomechanical modeling and nonlinear parameter estimation.pdf:PDF}
}
@Article{Anzt2012,
Title = {HiFlow 3: A Hardware-Aware Parallel Finite Element Package},
Author = {Anzt, H and Augustin, W and Baumann, M and Gengenbach, T and Hahn, T and Helfrich-Schkarbanenko, A and Heuveline, V and Ketelaer, E and Lukarski, D and Nestler, A and others},
Journal = {Tools for High Performance Computing 2011},
Year = {2012},
Pages = {139--151},
Publisher = {Springer}
}
@Article{Anzt2010,
Title = {{Energy efficiency of mixed precision iterative refinement methods using hybrid hardware platforms}},
Author = {Anzt, H. and Rocker, B. and Heuveline, V.},
Journal = {Computer Science-Research and Development},
Year = {2010},
Pages = {1--8},
ISSN = {1865-2034},
Publisher = {Springer}
}
@Article{Archip2007,
Title = {Non-rigid alignment of pre-operative MRI, fMRI, and DT-MRI with intra-operative MRI for enhanced visualization and navigation in image-guided neurosurgery},
Author = {Archip, Neculai and Clatz, Olivier and Whalen, Stephen and Kacher, Dan and Fedorov, Andriy and Kot, Andriy and Chrisochoides, Nikos and Jolesz, Ferenc and Golby, Alexandra and Black, Peter M and others},
Journal = {Neuroimage},
Year = {2007},
Number = {2},
Pages = {609--624},
Volume = {35},
Publisher = {Elsevier}
}
@Article{Arnold2002,
Title = {Unified analysis of discontinuous Galerkin methods for elliptic problems},
Author = {Arnold, Douglas N and Brezzi, Franco and Cockburn, Bernardo and Marini, L Donatella},
Journal = {SIAM journal on numerical analysis},
Year = {2002},
Number = {5},
Pages = {1749--1779},
Volume = {39},
Publisher = {SIAM}
}
@InProceedings{Asfour2013,
Title = {{ARMAR-4: A 63 DOF Torque Controlled Humanoid Robot}},
Author = {Tamim Asfour and Julian Schill and Heiner Peters and Cornelius Klas and Jens B\"ucker and Christian Sander and Stefan Schulz and Artem Kargov and Tino Werner and Volker Bartenbach},
Booktitle = {IEEE/RAS International Conference on Humanoid Robots (Humanoids)},
Year = {2013},
Address = {Atlanta, USA},
Month = {October},
Pages = {--},
Owner = {Tamim},
Timestamp = {2013.10.25}
}
@Article{BabarendaGamage2012,
Title = {Patient-Specific Modeling of Breast Biomechanics with Applications to Breast Cancer Detection and Treatment},
Author = {Babarenda Gamage, T.P. and Rajagopal, V. and Nielsen, P.M.F. and Nash, M.P.},
Journal = {Patient-Specific Modeling in Tomorrow's Medicine},
Year = {2012},
Pages = {379--412},
Publisher = {Springer}
}
@Article{Bacon2006,
Title = {The Surgical Simulation and Training Based Language for Medical Simulation},
Author = {Bacon, James and Tardella, Neil and Pratt, Janey and ENGLISH, John HUaand James},
Journal = {Medicine Meets Virtual Reality 14: Accelerating Change in Health Care: Next Medical Toolkit},
Year = {2006},
Pages = {37},
Volume = {119},
Publisher = {IOS Press}
}
@InProceedings{Baraff1996,
Title = {Linear-time dynamics using lagrange multipliers},
Author = {Baraff, D.},
Booktitle = {Proceedings of the 23rd annual conference on Computer graphics and interactive techniques},
Year = {1996},
Organization = {ACM},
Pages = {137--146}
}
@InProceedings{Baraff1998,
Title = {Large steps in cloth simulation},
Author = {Baraff, D. and Witkin, A.},
Booktitle = {Proceedings of the 25th annual conference on Computer graphics and interactive techniques},
Year = {1998},
Organization = {ACM},
Pages = {43--54}
}
@Article{Barbic2005,
Title = {{Real-time subspace integration for St. Venant-Kirchhoff deformable models}},
Author = {Barbi{\v{c}}, J. and James, D.L.},
Journal = {ACM Transactions on Graphics (TOG)},
Year = {2005},
Number = {3},
Pages = {990},
Volume = {24},
Abstract = {In this paper, we present an approach for fast subspace integration
of reduced-coordinate nonlinear deformable models that is suitable
for interactive applications in computer graphics and haptics. Our
approach exploits dimensional model reduction to build reducedcoordinate
deformable models for objects with complex geometry.
We exploit the fact that model reduction on large deformation
models with linear materials (as commonly used in graphics)
result in internal force models that are simply cubic polynomials
in reduced coordinates. Coefcients of these polynomials can be
precomputed, for efcient runtime evaluation. This allows simulation
of nonlinear dynamics using fast implicit Newmark subspace
integrators, with subspace integration costs independent of geometric
complexity. We present two useful approaches for generating
low-dimensional subspace bases: modal derivatives and an interactive
sketching technique. Mass-scaled principal component analysis
(mass-PCA) is suggested for dimensionality reduction. Finally,
several examples are given from computer animation to illustrate
high performance, including force-feedback haptic rendering of a
complicated object undergoing large deformations.},
File = {:D\:\\StefanIAIM\\Dokumente\\Literatur\\JabRef\\Surgery Simulation\\Real-Time Subspace Integration for St.Venant-Kirchhoff Deformable Models.pdf:PDF},
Publisher = {ACM}
}
@Article{Bartenbach2013,
Title = {The BioMotionBot: A robotic device for applications in human motor learning and rehabilitation },
Author = {V. Bartenbach and C. Sander and M. P\"oschl and K. Wilging and T. Nelius and F. Doll and W. Burger and C. Stockinger and A. Focke and T. Stein},
Journal = {Journal of Neuroscience Methods },
Year = {2013},
Number = {2},
Pages = {282 - 297},
Volume = {213},
Doi = {http://dx.doi.org/10.1016/j.jneumeth.2012.12.006},
ISSN = {0165-0270},
Keywords = {3D robotic manipulandum},
Url = {http://www.sciencedirect.com/science/article/pii/S0165027012004736}
}
@Article{Basdogan2007,
Title = {VR-Based Simulators for Training in Minimally Invasive Surgery},
Author = {Basdogan,, Cagatay and Sedef,, Mert and Harders,, Matthias and Wesarg,, Stefan},
Journal = {IEEE Comput. Graph. Appl.},
Year = {2007},
Number = {2},
Pages = {54--66},
Volume = {27},
Abstract = {Simulation-based training using
VR techniques is a promising
alternative to traditional
training in minimally invasive
surgery (MIS). Simulators let
the trainee touch, feel, and
manipulate virtual tissues and
organs through the same
surgical tool handles used in
actual MIS while viewing
images of tool-tissue
interactions on a monitor as in
real laparoscopic procedures.},
Address = {Los Alamitos, CA, USA},
Doi = {http://dx.doi.org/10.1109/MCG.2007.51},
File = {:Surgery Simulation\\VR-Based Simulators.pdf:PDF},
ISSN = {0272-1716},
Publisher = {IEEE Computer Society Press}
}
@Article{Bassi1997,
Title = {A high-order accurate discontinuous finite element method for the numerical solution of the compressible Navier--Stokes equations},
Author = {Bassi, Francesco and Rebay, Stefano},
Journal = {Journal of computational physics},
Year = {1997},
Number = {2},
Pages = {267--279},
Volume = {131},
Publisher = {Elsevier}
}
@Article{Bastian2009,
Title = {An unfitted finite element method using discontinuous Galerkin},
Author = {Bastian, Peter and Engwer, Christian},
Journal = {International journal for numerical methods in engineering},
Year = {2009},
Number = {12},
Pages = {1557--1576},
Volume = {79},
Publisher = {Wiley Online Library}
}
@Book{Bathe1996,
Title = {{Finite element procedures}},
Author = {Bathe, K.J.},
Publisher = {Prenctice Hall, Upper Saddle River [NJ]},
Year = {1996}
}
@Article{Baumhauer2008,
Title = {Navigation in endoscopic soft tissue surgery: perspectives and limitations},
Author = {Baumhauer, Matthias and Feuerstein, Marco and Meinzer, Hans-Peter and Rassweiler, J},
Journal = {Journal of Endourology},
Year = {2008},
Number = {4},
Pages = {751--766},
Volume = {22},
Publisher = {Mary Ann Liebert, Inc. 2 Madison Avenue Larchmont, NY 10538 USA}
}
@Article{Belgihiti2000,
Title = {The Brisbane 2000 terminology of liver anatomy and resections},
Author = {Belgihiti, J and Clavien, PA and Gadzijev, E and Garden, JO and Lau, W and Makuuchi, M and others},
Journal = {Hpb},
Year = {2000},
Number = {3},
Pages = {333--339},
Volume = {2}
}
@Book{Belytschko2000,
Title = {Nonlinear finite elements for continua and structures},
Author = {Belytschko, T. and Liu, WK and Moran, B.},
Publisher = {Wiley},
Year = {2000},
Volume = {36}
}
@InCollection{Bendl1993,
Title = {VIRTUOS - A program for VIRTUal radiotherapy Simulation},
Author = {Bendl, Rolf and Pross, J{\"u}rgen and Keller, Mark and B{\"u}rkelbach, Josef and Schlegel, Wolfgang},
Booktitle = {Computer Assisted Radiology/Computergest{\"u}tzte Radiologie},
Publisher = {Springer},
Year = {1993},
Pages = {676--682}
}
@Article{Benzi2002,
Title = {Preconditioning techniques for large linear systems: a survey},
Author = {Benzi, M.},
Journal = {Journal of Computational Physics},
Year = {2002},
Number = {2},
Pages = {418--477},
Volume = {182},
Publisher = {Elsevier}
}
@Article{Benzi1996,
Title = {A sparse approximate inverse preconditioner for the conjugate gradient method},
Author = {Benzi, M. and Meyer, C.D. and Tuma, M. and others},
Journal = {SIAM Journal on Scientific Computing},
Year = {1996},
Number = {5},
Pages = {1135--1149},
Volume = {17},
Publisher = {Philadelphia, PA: SIAM, c1993-}
}
@Booklet{BernardoCockburn1999,
Title = {The development of discontinuous Galerkin methods},
Author = {Bernardo Cockburn,George E. Karniadakis,Chi-wang Shu},
Year = {1999},
Abstract = {. In this paper, we present an overview of the evolution of the discontinuous Galerkin methods since their introduction in 1973 by Reed and Hill, in the framework of neutron transport, until their most recent developments. We show how these methods made their way into the main stream of computational fluid dynamics and how they are quickly finding use in a wide variety of applications. We review the theoretical and algorithmic aspects of these methods as well as their applications to equations including nonlinear conservation laws, the compressible Navier-Stokes equations, and Hamilton-Jacobi-like equations. 1 Introduction Problems of practical interest in which convection plays an important role arise in applications as diverse as meteorology, weather-forecasting, oceanography, gas dynamics, aeroacoustics, turbomachinery, turbulent flows, granular flows, oil recovery simulation, modeling of shallow water, transport of contaminant in porous media, viscoelastic flows, semiconductor de...},
File = {:Biomechanical Models\\DG-FEM\\The development of discontinuous Galerkin Method.pdf:PDF},
Institution = {CiteSeerX - Scientific Literature Digital Library and Search Engine [http://citeseerx.ist.psu.edu/oai2] (United States)},
Keywords = {Bernardo Cockburn,George E. Karniadakis,Chi-wang Shu The development of discontinuous Galerkin methods},
Publisher = {unknown},
Url = {http://citeseer.ist.psu.edu/428068.html}
}
@Article{Bharatha2001,
Title = {{Evaluation of three-dimensional finite element-based deformable registration of pre-and intraoperative prostate imaging}},
Author = {Bharatha, A. and Hirose, M. and Hata, N. and Warfield, S.K. and Ferrant, M. and Zou, K.H. and Suarez-Santana, E. and Ruiz-Alzola, J. and DAmico, A. and Cormack, R.A. and others},
Journal = {Medical Physics},
Year = {2001},
Pages = {2551},
Volume = {28},
Abstract = {Two major factors preventing the routine clinical use
of finite-element analysis for image registration are: 1) the substantial
labor required to construct a finite-element model for an individual
patients anatomy and 2) the difficulty of determining an
appropriate set of finite-element boundary conditions. This paper
addresses these issues by presenting algorithms that automatically
generate a high quality hexahedral finite-element mesh and automatically
calculate boundary conditions for an imaged patient.
Medial shape models called m-reps are used to facilitate these tasks
and reduce the effort required to apply finite-element analysis to
image registration. Encouraging results are presented for the registration
of CT image pairs which exhibit deformation caused by
pressure from an endorectal imaging probe and deformation due
to swelling.},
File = {:Image-Guided Surgery\\Automated Finite-Element Analysis for Deformable Registration of Prostate Images.pdf:PDF}
}
@Booklet{Bianchi2004,
Title = {{Simultaneous topology and stiffness identification for mass-spring models based on fem reference deformations}},
Author = {Bianchi, G. and Solenthaler, B. and Szekely, G. and Harders, M.},
Year = {2004},
Abstract = {Mass-spring systems are of special interest for soft tissue
modeling in surgical simulation due to their ease of implementation and
real-time behavior. However, the parameter identification (masses, spring
constants, mesh topology) still remains a challenge. In previous work, we
proposed an approach based on the training of mass-spring systems according
to known reference models. Our initial focus was the determination
of mesh topology in 2D. In this paper, we extend the method to 3D.
Furthermore, we introduce a new approach to simultaneously identify
mesh topology and spring stiffness values. Linear elastic FEM deformation
computations are used as reference. Additionally, our results show
that uniform distributions of spring stiffness constants fails to simulate
linear elastic deformations.},
File = {:Biomechanical Models\\Mass-Spring\\Simultaneous Topology and Stiffness Identification for Mass-Spring Models Based on FEM Reference Deformations.pdf:PDF},
Journal = {Lecture Notes in Computer Science},
Pages = {293--301},
Publisher = {Springer}
}
@Article{Bielser2004,
Title = {A state machine for real-time cutting of tetrahedral meshes},
Author = {Bielser, Daniel and Glardon, Pascal and Teschner, Matthias and Gross, Markus},
Journal = {Graphical Models},
Year = {2004},
Number = {6},
Pages = {398--417},
Volume = {66},
Publisher = {Elsevier}
}
@InCollection{Bilger2011,
Title = {Biomechanical simulation of electrode migration for deep brain stimulation},
Author = {Bilger, Alexandre and Dequidt, J{\'e}r{\'e}mie and Duriez, Christian and Cotin, St{\'e}phane},
Booktitle = {Medical Image Computing and Computer-Assisted Intervention--MICCAI 2011},
Publisher = {Springer},
Year = {2011},
Pages = {339--346}
}
@InProceedings{Bodenstedt2012,
Title = {Evaluation of a Learning-based Partially Automated Approach for Assistance in Tele-Robotic Manipulation},
Author = {S. Bodenstedt and N. Padoy and GD. Hager},
Booktitle = {M2CAI MICCAI Workshop: Modeling and Monitoring of Computer Assisted Interventions},
Year = {2012},
Owner = {Stefanie},
Timestamp = {2012.12.19}
}
@InProceedings{Bodenstedt2012a,
Title = {Learned Partial Automation for Shared Control in Tele-Robotic Manipulation},
Author = {S. Bodenstedt and N. Padoy and GD. Hager},
Booktitle = {AAAI Fall Symposium on Robots Learning Interactively from Human Teachers},
Year = {2012},
Owner = {Stefanie},
Timestamp = {2012.12.19}
}
@InProceedings{Bodenstedt2011,
Title = {A flexible framework for multiple sensor integration into a context-aware CAS-system},
Author = {Bodenstedt, S. and Roehl, S. and Suwelack, S. and Katic, D. and Dillmann, R. and Müller-Stich, B. and Speidel, S.},
Booktitle = {Proc. Computer Assisted Radiology and Surgery (CARS)},
Year = {2011}
}
@Article{Bogatyrenko2011,
Title = {Efficient physics-based tracking of heart surface motion for beating heart surgery robotic systems},
Author = {Bogatyrenko, Evgeniya and Pompey, Pascal and Hanebeck, Uwe D},
Journal = {International journal of computer assisted radiology and surgery},
Year = {2011},
Number = {3},
Pages = {387--399},
Volume = {6},
Publisher = {Springer}
}
@Book{Bonet1997,
Title = {Nonlinear continuum mechanics for finite element analysis},
Author = {Bonet, Javier},
Publisher = {Cambridge university press},
Year = {1997}
}
@Other{Box2000,
Title = {Simple object access protocol (SOAP) 1.1},
Author = {Box, D. and Ehnebuske, D. and Kakivaya, G. and Layman, A. and Mendelsohn, N. and Nielsen, H.F. and Thatte, S. and Winer, D.},
HowPublished = {http://www.w3.org/TR/SOAP/},
Month = May,
Year = {2000}
}
@Book{Braess2007,
Title = {Finite elements: Theory, fast solvers, and applications in solid mechanics},
Author = {Braess, Dietrich},
Publisher = {Cambridge University Press},
Year = {2007}
}
@Book{Braess2001,
Title = {Finite elements: Theory, fast solvers, and applications in solid mechanics},
Author = {Braess, Dietrich},
Publisher = {Cambridge University Press},
Year = {2001}
}
@Article{Brock2005,
Title = {Accuracy of finite element model-based multi-organ deformable image registration},
Author = {Brock, KK and Sharpe, MB and Dawson, LA and Kim, SM and Jaffray, DA},
Journal = {Medical physics},
Year = {2005},
Pages = {1647},
Volume = {32}
}
@Article{Bro-Nielsen1996,
Title = {{Real-time volumetric deformable models for surgery simulation using finite elements and condensation}},
Author = {Bro-Nielsen, M. and Cotin, S.},
Year = {1996},
Number = {3},
Pages = {57--66},
Volume = {15},
Abstract = {This paper discusses the application of 3D solid volumetric Finite Element models to surgery
simulation. In particular it presents three new approaches to the problem of achieving real-time
performance for these models. The simulation system we have developed is described and we
demonstrate real-time deformation using the methods developed in the paper.},
Booktitle = {Computer Graphics Forum},
File = {:D\:\\StefanIAIM\\Dokumente\\Literatur\\JabRef\\Surgery Simulation\\Real-time Volumetric Deformable MOdels for Surgery Simulation using Finite Elements and Condensation.pdf:PDF},
Organization = {Citeseer}
}
@InProceedings{Caan2010,
Title = {Gridifying a Diffusion Tensor Imaging Analysis Pipeline},
Author = {Caan, M.W.A. and Vos, F.M. and van Kampen, A.H.C. and Olabarriaga, S.D. and van Vliet, L.J.},
Booktitle = {Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing},
Year = {2010},
Organization = {IEEE Computer Society},
Pages = {733--738}
}
@Book{Carey1997,
Title = {The annotated VRML 2.0 reference manual},
Author = {Carey, Rikk and Bell, Gavin},
Publisher = {Addison-Wesley Longman Ltd.},
Year = {1997}
}
@Article{Carter2005,
Title = {{Application of soft tissue modelling to image-guided surgery}},
Author = {Carter, T.J. and Sermesant, M. and Cash, D.M. and Barratt, D.C. and Tanner, C. and Hawkes, D.J.},
Journal = {Medical Engineering and Physics},
Year = {2005},
Number = {10},
Pages = {893--909},
Volume = {27},
Abstract = {The deformation of soft tissue compromises the accuracy of image-guided surgery based on preoperative images, and restricts its applicability
to surgery on or near bony structures. One way to overcome these limitations is to combine biomechanical models with sparse intraoperative
data, in order to realistically warp the preoperative image to match the surgical situation.We detail the process of biomechanical modelling in
the context of image-guided surgery.We focus in particular on the finite element method, which is shown to be a promising approach, and review
the constitutive relationships which have been suggested for representing tissue during surgery. Appropriate intraoperative measurements are
required to constrain the deformation, and we discuss the potential of the modalities which have been applied to this task. This technology is
on the verge of transition into clinical practice, where it promises to increase the guidance accuracy and facilitate less invasive interventions.
We describe here how soft tissue modelling techniques have been applied to image-guided surgery applications.},
File = {:Image-Guided Surgery\\Application of soft tissue modelling to image-guided surgery.pdf:PDF},
Publisher = {Elsevier}
}
@Article{Cash2007,
Title = {{Concepts and preliminary data toward the realization of image-guided liver surgery}},
Author = {Cash, D.M. and Miga, M.I. and Glasgow, S.C. and Dawant, B.M. and Clements, L.W. and Cao, Z. and Galloway, R.L. and Chapman, W.C.},
Journal = {Journal of Gastrointestinal Surgery},
Year = {2007},
Number = {7},
Pages = {844--859},
Volume = {11},
Abstract = {Image-guided surgery provides navigational assistance to the surgeon by displaying the surgical probe position
on a set of preoperative tomograms in real time. In this study, the feasibility of implementing image-guided surgery
concepts into liver surgery was examined during eight hepatic resection procedures. Preoperative tomographic image data
were acquired and processed. Accompanying intraoperative data on liver shape and position were obtained through
optically tracked probes and laser range scanning technology. The preoperative and intraoperative representations of the
liver surface were aligned using the iterative closest point surface matching algorithm. Surface registrations resulted in mean
residual errors from 2 to 6 mm, with errors of target surface regions being below a stated goal of 1 cm. Issues affecting
registration accuracy include liver motion due to respiration, the quality of the intraoperative surface data, and intraoperative
organ deformation. Respiratory motion was quantified during the procedures as cyclical, primarily along the cranialcaudal
direction. The resulting registrations were more robust and accurate when using laser range scanning to rapidly acquire
thousands of points on the liver surface and when capturing unique geometric regions on the liver surface, such as the
inferior edge. Finally, finite element models recovered much of the observed intraoperative deformation, further decreasing
errors in the registration. Image-guided liver surgery has shown the potential to provide surgeons with important navigation
aids that could increase the accuracy of targeting lesions and the number of patients eligible for surgical resection.},
File = {:Image-Guided Surgery\\Concepts and Preliminary Data Toward the Realization of Image-guided Liver Surgery.pdf:PDF},
Publisher = {Springer}
}
@Article{Cash2005,
Title = {{Compensating for intraoperative soft-tissue deformations using incomplete surface data and finite elements}},
Author = {Cash, D.M. and Miga, M.I. and Sinha, T.K. and Galloway, R.L. and Chapman, W.C.},
Journal = {IEEE transactions on medical imaging},
Year = {2005},
Number = {11},
Pages = {1479--1491},
Volume = {24},
Abstract = {Image-guided liver surgery requires the ability to
identify and compensate for soft tissue deformation in the organ.
The predeformed state is represented as a complete three-dimensional
surface of the organ, while the intraoperative data is a range
scan point cloud acquired from the exposed liver surface. The first
step is to rigidly align the coordinate systems of the intraoperative
and preoperative data. Most traditional rigid registration methods
minimize an error metric over the entire data set. In this paper, a
new deformation-identifying rigid registration (DIRR) is reported
that identifies and aligns minimally deformed regions of the data
using a modified closest point distance cost function. Once a rigid
alignment has been established, deformation is accounted for using
a linearly elastic finite element model (FEM) and implemented
using an incremental framework to resolve geometric nonlinearities.
Boundary conditions for the incremental formulation are
generated from intraoperatively acquired range scan surfaces
of the exposed liver surface. A series of phantom experiments is
presented to assess the fidelity of the DIRR and the combined
DIRR/FEM approaches separately. The DIRR approach identified
deforming regions in 90% of cases under conditions of realistic
surgical exposure. With respect to the DIRR/FEM algorithm,
subsurface target errors were correctly located to within 4 mm in
phantom experiments.},
File = {:D\:\\StefanIAIM\\Dokumente\\Literatur\\JabRef\\Image-Guided Surgery\\Compensating for intraoperative soft-tissue deformations using incomplete surface data and finite elements.pdf:PDF},
Publisher = {New York, NY: Institute of Electrical and Electronics Engineers, c1982-}
}
@Article{Castillo2009,
Title = {A framework for evaluation of deformable image registration spatial accuracy using large landmark point sets},
Author = {Castillo, Richard and Castillo, Edward and Guerra, Rudy and Johnson, Valen E and McPhail, Travis and Garg, Amit K and Guerrero, Thomas},
Journal = {Physics in Medicine and Biology},
Year = {2009},
Number = {7},
Pages = {1849},
Volume = {54},
Publisher = {IOP Publishing}
}
@InCollection{Chabanas2004,
Title = {Physical model language: Towards a unified representation for continuous and discrete models},
Author = {Chabanas, Matthieu and Promayon, Emmanuel},
Booktitle = {Medical Simulation},
Publisher = {Springer},
Year = {2004},
Pages = {256--266}
}
@InCollection{Chang2013,
Title = {Real-Time Dense Stereo Reconstruction Using Convex Optimisation with a Cost-Volume for Image-Guided Robotic Surgery},
Author = {Chang, Ping-Lin and Stoyanov, Danail and Davison, Andrew J and others},
Booktitle = {Medical Image Computing and Computer-Assisted Intervention--MICCAI 2013},
Publisher = {Springer},
Year = {2013},
Pages = {42--49}
}
@Article{Chentanez2009,
Title = {{Interactive simulation of surgical needle insertion and steering}},
Author = {Chentanez, N. and Alterovitz, R. and Ritchie, D. and Cho, L. and Hauser, K. and Goldberg, K. and Shewchuk, J. and OBrien, J.},
Year = {2009},
Abstract = {We present algorithms for simulating and visualizing the insertion
and steering of needles through deformable tissues for surgical
training and planning. Needle insertion is an essential component
of many clinical procedures such as biopsies, injections, neurosurgery,
and brachytherapy cancer treatment. The success of these
procedures depends on accurate guidance of the needle tip to a clinical
target while avoiding vital tissues. Needle insertion deforms
body tissues, making accurate placement difficult. Our interactive
needle insertion simulator models the coupling between a steerable
needle and deformable tissue. We introduce (1) a novel algorithm
for local remeshing that quickly enforces the conformity of a tetrahedral
mesh to a curvilinear needle path, enabling accurate computation
of contact forces, (2) an efficient method for coupling a 3D
finite element simulation with a 1D inextensible rod with stick-slip
friction, and (3) optimizations that reduce the computation time for
physically based simulations. We can realistically and interactively
simulate needle insertion into a prostate mesh of 13,375 tetrahedra
and 2,763 vertices at a 25 Hz frame rate on an 8-core 3.0 GHz Intel
Xeon PC. The simulation models prostate brachytherapy with
needles of varying stiffness, steering needles around obstacles, and
supports motion planning for robotic needle insertion. We evaluate
the accuracy of the simulation by comparing against real-world
experiments in which flexible, steerable needles were inserted into
gel tissue phantoms.
Keywords: surgical simulation,},
Booktitle = {ACM SIGGRAPH},
File = {:D\:\\StefanIAIM\\Dokumente\\Literatur\\JabRef\\Biomechanical Models\\Co-Rotational\\Interactive Simulation of Surgical Needle Insertion and Steering.pdf:PDF}
}
@Conference{Chrisochoides2006,
Title = {{Toward real-time image guided neurosurgery using distributed and grid computing}},
Author = {Chrisochoides, N. and Fedorov, A. and Kot, A. and Archip, N. and Black, P. and Clatz, O. and Golby, A. and Kikinis, R. and Warfield, S.K.},
Booktitle = {Proceedings of the 2006 ACM/IEEE conference on Supercomputing},
Year = {2006},
Organization = {ACM},
Pages = {76}
}
@Article{Chuang2001,
Title = {Shape matching and recognition using a physically based object model},
Author = {Chuang, Jen-Hui and Sheu, Jin-Fa and Lin, Chien-Chou and Yang, Hui-Kuo},
Journal = {Computers \& Graphics},
Year = {2001},
Number = {2},
Pages = {211--222},
Volume = {25},
Publisher = {Elsevier}
}
@Article{Chui2003,
Title = {A new point matching algorithm for non-rigid registration},
Author = {Chui, H. and Rangarajan, A.},
Journal = {Computer Vision and Image Understanding},
Year = {2003},
Number = {2},
Pages = {114--141},
Volume = {89},
Publisher = {Elsevier}
}
@Article{Cifuentes1992,
Title = {A performance study of tetrahedral and hexahedral elements in 3-D finite element structural analysis},
Author = {Cifuentes, AO and Kalbag, A.},
Journal = {Finite Elements in Analysis and Design},
Year = {1992},
Number = {3},
Pages = {313--318},
Volume = {12},
Publisher = {Elsevier}
}
@InProceedings{Cignoni2008,
Title = {Meshlab: an open-source mesh processing tool},
Author = {Cignoni, Paolo and Callieri, Marco and Corsini, Massimiliano and Dellepiane, Matteo and Ganovelli, Fabio and Ranzuglia, Guido},
Booktitle = {Eurographics Italian Chapter Conference},
Year = {2008},
Organization = {The Eurographics Association},
Pages = {129--136}
}
@Article{Clatz2005,
Title = {{Robust nonrigid registration to capture brain shift from intraoperative MRI}},
Author = {Clatz, O. and Delingette, H. and Talos, I.F. and Golby, AJ and Kikinis, R. and Jolesz, FA and Ayache, N. and Warfield, SK and INRIA, F.},
Journal = {IEEE Transactions on medical imaging},
Year = {2005},
Number = {11},
Pages = {1417--1427},
Volume = {24},
Abstract = {We present a new algorithm to register 3-D preoperative
magnetic resonance (MR) images to intraoperativeMRimages
of the brain which have undergone brain shift. This algorithm relies
on a robust estimation of the deformation from a sparse noisy
set of measured displacements. We propose a new framework to
compute the displacement field in an iterative process, allowing
the solution to gradually move from an approximation formulation
(minimizing the sum of a regularization term and a data error
term) to an interpolation formulation (least square minimization
of the data error term). An outlier rejection step is introduced in
this gradual registration process using a weighted least trimmed
squares approach, aiming at improving the robustness of the algorithm.
We use a patient-specific model discretized with the finite
element method in order to ensure a realistic mechanical behavior
of the brain tissue.
To meet the clinical time constraint, we parallelized the slowest
step of the algorithm so that we can perform a full 3-D image registration
in 35 s (including the image update time) on a heterogeneous
cluster of 15 personal computers. The algorithm has been
tested on six cases of brain tumor resection, presenting a brain shift
of up to 14 mm. The results show a good ability to recover large
displacements, and a limited decrease of accuracy near the tumor
resection cavity.},
File = {:Image-Guided Surgery\\Robust Nonrigid Registration to Capture Brain Shift.pdf:PDF}
}
@Article{Cleary2010,
Title = {Image-guided interventions: technology review and clinical applications},
Author = {Cleary, Kevin and Peters, Terry M},
Journal = {Annual review of biomedical engineering},
Year = {2010},
Pages = {119--142},
Volume = {12},
Publisher = {Annual Reviews}
}
@Article{Clements2008,
Title = {Robust surface registration using salient anatomical features for image-guided liver surgery: Algorithm and validation},
Author = {Clements, Logan W and Chapman, William C and Dawant, Benoit M and Galloway Jr, Robert L and Miga, Michael I},
Journal = {Medical Physics},
Year = {2008},
Pages = {2528},
Volume = {35}
}
@InProceedings{Clements2007,
Title = {Atlas-based method for model updating in image-guided liver surgery},
Author = {Clements, Logan W. and Dumpuri, Prashanth and Chapman, William C. and Galloway, Robert L. and Miga, Michael I.},
Booktitle = {Medical Imaging 2007: Visualization and Image-Guided Procedures},
Year = {2007},
Editor = {Cleary, Kevin R. and Miga, Michael I.},
Pages = {650917+},
Publisher = {SPIE},
Volume = {6509},
Abstract = {Similar to the well documented brain shift experienced during neurosurgical procedures, intra-operative soft tissue deformation in open hepatic resections is the primary source of error in current image-guided liver surgery (IGLS) systems. The use of bio-mechanical models has shown promise in providing the link between the deformed, intra-operative patient anatomy and the pre-operative image data. More specifically, the current protocol for deformation compensation in IGLS involves the determination of displacements via registration of intra-operatively acquired sparse data and subsequent use of the displacements to drive solution of a linear elastic model via the finite element method (FEM). However, direct solution of the model during the surgical procedure has several logistical limitations including computational time and the ability to accurately prescribe boundary conditions and material properties. Recently, approaches utilizing an atlas of pre-operatively computed model solutions based on a priori information concerning the surgical loading conditions have been proposed as a more realistic avenue for intra-operative deformation compensation. Similar to previous work, we propose the use of a simple linear inverse model to match the intra-operatively acquired data to the pre-operatively computed atlas. Additionally, an iterative approach is implemented whereby point correspondence is updated during the matching process, being that the correspondence between intra-operative data and the pre-operatively computed atlas is not explicitly known in liver applications. Preliminary validation experiments of the proposed algorithm were performed using both simulation and phantom data. The proposed method provided comparable results in the phantom experiments with those obtained using the traditional incremental FEM approach.},
Citeulike-article-id = {6496263},
Citeulike-linkout-0 = {http://scitation.aip.org/getabs/servlet/GetabsServlet?prog=normal\&id=PSISDG006509000001650917000001\&idtype=cvips\&gifs=yes},
Citeulike-linkout-1 = {http://link.aip.org/link/?PSI/6509/650917},
Location = {San Diego, CA, USA},
Posted-at = {2010-01-06 17:11:21},
Priority = {2},
Url = {http://scitation.aip.org/getabs/servlet/GetabsServlet?prog=normal\&id=PSISDG006509000001650917000001\&idtype=cvips\&gifs=yes}
}
@Article{Clifford2002,
Title = {Assessment of hepatic motion secondary to respiration for computer assisted interventions},
Author = {Clifford, Mark A and Banovac, Filip and Levy, Elliot and Cleary, Kevin},
Journal = {Computer Aided Surgery},
Year = {2002},
Number = {5},
Pages = {291--299},
Volume = {7},
Publisher = {Wiley Online Library}
}
@Article{Coles2011,
Title = {The role of haptics in medical training simulators: a survey of the state of the art},
Author = {Coles, Timothy R and Meglan, Dwight and John, Nigel W},
Journal = {Haptics, IEEE Transactions on},
Year = {2011},
Number = {1},
Pages = {51--66},
Volume = {4},
Publisher = {IEEE}
}
@Article{Conti2005,
Title = {CHAI: An Open-Source Library for the Rapid Development of Haptic Scenes},
Author = {Conti, Fran{\c{c}}ois and Barbagli, Federico and Morris, Dan and Sewell, Christopher},
Year = {2005}
}
@Article{Cotin2000,
Title = {{A hybrid elastic model for real-time cutting, deformations, and force feedback for surgery training and simulation}},
Author = {Cotin, S. and Delingette, H. and Ayache, N.},
Journal = {The Visual Computer},
Year = {2000},
Number = {8},
Pages = {437--452},
Volume = {16},
Abstract = {We propose three physical models based on
linear elasticity theory and finite-element
modeling that are well-suited for surgery
simulation. The first model combines precomputed
deformations to deform large size
meshes in real-time, but cannot make any
topological changes to the mesh. The second
model is similar to the spring-mass models
where volumetric deformations and cutting
operations can be simulated on small meshes
in real time. Finally, we have developped
a third method, combining the previous two
solutions into a hybrid model that simulates
deformations and cutting on complex
anatomical structures.},
File = {:D\:\\StefanIAIM\\Dokumente\\Literatur\\JabRef\\Surgery Simulation\\A hybrid elastic model for real-time cutting, deformations, and force feedback for surgery training and simulation.pdf:PDF},
Publisher = {Springer}
}
@InBook{Cotin1999,
Title = {{Real-time elastic deformations of soft tissues for surgerysimulation}},
Author = {Cotin, S. and Delingette, H. and Ayache, N.},
Pages = {62--73},
Year = {1999},
Number = {1},
Volume = {5},
Abstract = {In this paper, we describe a new method for surgery simulation including a volumetric model built from medical images
and an elastic modeling of the deformations. The physical model is based on elasticity theory which suitably links the shape of
deformable bodies and the forces associated with the deformation. A real-time computation of the deformation is possible thanks tc
a preprocessing of elementary deformations derived from a finite element method. This method has been implemented in a system
including a force feedback device and a collision detection algorithm. The simulator works in real-time with a high resolution liver
model.},
File = {:Biomechanical Models\\Standard FEM\\Real-Time Elastic Deformations of Soft Tissues for Surgery Simulation.pdf:PDF},
Journal = {IEEE transactions on Visualization and Computer Graphics}
}
@Conference{Cotin2008,
Title = {{Efficient nonlinear FEM for soft tissue modelling and its GPU implementation within the open source framework SOFA}},
Author = {Cotin, S. and Passenger, J.},
Booktitle = {Biomedical Simulation: 4th International Symposium, Isbms 2008, London, Uk, July 7-8, 2008, Proceedings},
Year = {2008},
Organization = {Springer-Verlag New York Inc},
Pages = {28}
}
@InProceedings{Courtecuisse2010,
Title = {Asynchronous preconditioners for efficient solving of non-linear deformations},
Author = {Courtecuisse, H. and Allard, J. and Duriez, C. and Cotin, S. and others},
Booktitle = {VRIPHYS-Virtual Reality Interaction and Physical Simulation},
Year = {2010},
Pages = {59--68}
}
@Article{Courtecuisse2013,
Title = {Real-time simulation of contact and cutting of heterogeneous soft-tissues},
Author = {Courtecuisse, Hadrien and Allard, J{\'e}r{\'e}mie and Kerfriden, Pierre and Bordas, St{\'e}phane and Cotin, St{\'e}phane and Duriez, Christian},
Journal = {Medical image analysis},
Year = {2013},
Publisher = {Elsevier}
}
@Article{Courtecuisse2010a,
Title = {GPU-based real-time soft tissue deformation with cutting and haptic feedback},
Author = {Courtecuisse, H. and Jung, H. and Allard, J. and Duriez, C. and Lee, D.Y. and Cotin, S.},
Journal = {Progress in biophysics and molecular biology},
Year = {2010},
Number = {2},
Pages = {159--168},
Volume = {103},
Publisher = {Elsevier}
}
@Article{Crouch2007,
Title = {{Automated finite-element analysis for deformable registration of prostate images.}},
Author = {Crouch, JR and Pizer, SM and Chaney, EL and Hu, YC and Mageras, GS and Zaider, M.},
Journal = {IEEE Transactions on medical imaging},
Year = {2007},
Number = {10},
Pages = {1379},
Volume = {26}
}
@Article{Dawood2007,
Title = {{Respiratory gating in positron emission tomography: a quantitative comparison of different gating schemes}},
Author = {Dawood, M. and B{\\"u}ther, F. and Lang, N. and Schober, O. and Sch{\\"a}fers, K.P.},
Journal = {Medical physics},
Year = {2007},
Pages = {3067},
Volume = {34}
}
@Article{Dehnavi2012,
Title = {Parallel Sparse Approximate Inverse Preconditioning on Graphic Processing Units},
Author = {Maryam Mehri Dehnavi and David Fernandez and Jean-Luc Gaudiot and Dennis Giannacopoulos},
Journal = {IEEE Transactions on Parallel and Distributed Systems},
Year = {2012},
Number = {PrePrints},
Pages = {1},
Volume = {99},
Address = {Los Alamitos, CA, USA},
Doi = {http://doi.ieeecomputersociety.org/10.1109/TPDS.2012.286},
ISSN = {1045-9219},
Publisher = {IEEE Computer Society}
}
@Article{Delingette2006,
Title = {{Computational models for image-guided robot-assisted and simulated medical interventions}},
Author = {Delingette, H. and Pennec, X. and Soler, L. and Marescaux, J. and Ayache, N.},
Journal = {PROCEEDINGS-IEEE},
Year = {2006},
Number = {9},
Pages = {1678},
Volume = {94},
Abstract = {Medical image analysis plays a crucial role in the
diagnosis, planning, control, and follow-up of therapy. To be