11,854 research outputs found
Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery
One of the main challenges for computer-assisted surgery (CAS) is to determine the intra-opera- tive morphology and motion of soft-tissues. This information is prerequisite to the registration of multi-modal patient-specific data for enhancing the surgeon’s navigation capabilites by observ- ing beyond exposed tissue surfaces and for providing intelligent control of robotic-assisted in- struments. In minimally invasive surgery (MIS), optical techniques are an increasingly attractive approach for in vivo 3D reconstruction of the soft-tissue surface geometry. This paper reviews the state-of-the-art methods for optical intra-operative 3D reconstruction in laparoscopic surgery and discusses the technical challenges and future perspectives towards clinical translation. With the recent paradigm shift of surgical practice towards MIS and new developments in 3D opti- cal imaging, this is a timely discussion about technologies that could facilitate complex CAS procedures in dynamic and deformable anatomical regions
The multiplicative deformation split for shells with application to growth, chemical swelling, thermoelasticity, viscoelasticity and elastoplasticity
This work presents a general unified theory for coupled nonlinear elastic and
inelastic deformations of curved thin shells. The coupling is based on a
multiplicative decomposition of the surface deformation gradient. The
kinematics of this decomposition is examined in detail. In particular, the
dependency of various kinematical quantities, such as area change and
curvature, on the elastic and inelastic strains is discussed. This is essential
for the development of general constitutive models. In order to fully explore
the coupling between elastic and different inelastic deformations, the surface
balance laws for mass, momentum, energy and entropy are examined in the context
of the multiplicative decomposition. Based on the second law of thermodynamics,
the general constitutive relations are then derived. Two cases are considered:
Independent inelastic strains, and inelastic strains that are functions of
temperature and concentration. The constitutive relations are illustrated by
several nonlinear examples on growth, chemical swelling, thermoelasticity,
viscoelasticity and elastoplasticity of shells. The formulation is fully
expressed in curvilinear coordinates leading to compact and elegant expressions
for the kinematics, balance laws and constitutive relations
Estimating and understanding motion : from diagnostic to robotic surgery
Estimating and understanding motion from an image sequence is a central topic in computer vision. The high interest in this topic is because we are living in a world where many events that occur in the environment are dynamic. This makes motion estimation and understanding a natural component and a key factor in a widespread of applications including object recognition , 3D shape reconstruction, autonomous navigation and medica! diagnosis.
Particularly, we focus on the medical domain in which understanding the human body for clinical purposes requires retrieving the organs' complex motion patterns, which is in general a hard problem when using only image data. In this thesis, we cope with this problem by posing the question - How to achieve a realistic motion estimation to offer a better clinical understanding? We focus this thesis on answering this question by using a variational formulation as a basis to understand one of the most complex motions in the human's body, the heart motion, through three different applications: (i) cardiac motion estimation for diagnostic, (ii) force estimation and (iii) motion prediction, both for robotic surgery.
Firstly, we focus on a central topic in cardiac imaging that is the estimation of the cardiac motion. The main aim is to offer objective and understandable measures to physicians for helping them in the diagnostic of cardiovascular diseases. We employ ultrafast ultrasound data and tools for imaging motion drawn from diverse areas such as low-rank analysis and variational deformation to perform a realistic cardiac motion estimation. The significance is that by taking low-rank data with carefully chosen penalization, synergies in this complex variational problem can be created. We demonstrate how our proposed solution deals with complex deformations through careful numerical experiments using realistic and simulated data.
We then move from diagnostic to robotic surgeries where surgeons perform delicate procedures remotely through robotic manipulators without directly interacting with the patients. As a result, they lack force feedback, which is an important primary sense for increasing surgeon-patient transparency and avoiding injuries and high mental workload. To solve this problem, we follow the conservation principies of continuum mechanics in which it is clear that the change in shape of an elastic object is directly proportional to the force applied. Thus, we create a variational framework to acquire the deformation that the tissues undergo due to an applied force. Then, this information is used in a learning system to find the nonlinear relationship between the given data and the applied force. We carried out experiments with in-vivo and ex-vivo data and combined statistical, graphical and perceptual analyses to demonstrate the strength of our solution.
Finally, we explore robotic cardiac surgery, which allows carrying out complex procedures including Off-Pump Coronary Artery Bypass Grafting (OPCABG). This procedure avoids the associated complications of using Cardiopulmonary Bypass (CPB) since the heart is not arrested while performing the surgery on a beating heart. Thus, surgeons have to deal with a dynamic target that compromisetheir dexterity and the surgery's precision. To compensate the heart motion, we propase a solution composed of three elements: an energy function to estimate the 3D heart motion, a specular highlight detection strategy and a prediction approach for increasing the robustness of the solution. We conduct evaluation of our solution using phantom and realistic datasets.
We conclude the thesis by reporting our findings on these three applications and highlight the dependency between motion estimation and motion understanding at any dynamic event, particularly in clinical scenarios.L’estimació i comprensió del moviment dins d’una seqüència d’imatges és un tema central en la visió per ordinador, el que genera un gran interès perquè vivim en un entorn ple d’esdeveniments dinà mics. Per aquest motiu és considerat com un component natural i factor clau dins d’un ampli ventall d’aplicacions, el qual inclou el reconeixement d’objectes, la reconstrucció de formes tridimensionals, la navegació autònoma i el diagnòstic de malalties.
En particular, ens situem en l’à mbit mèdic en el qual la comprensiĂł del cos humĂ , amb finalitats clĂniques, requereix l’obtenciĂł de patrons complexos de moviment dels òrgans. Aquesta Ă©s, en general, una tasca difĂcil quan s’utilitzen nomĂ©s dades de tipus visual. En aquesta tesi afrontem el problema plantejant-nos la pregunta - Com es pot aconseguir una estimaciĂł realista del moviment amb l’objectiu d’oferir una millor comprensiĂł clĂnica? La tesi se centra en la resposta mitjançant l’ús d’una formulaciĂł variacional com a base per entendre un dels moviments mĂ©s complexos del cos humĂ , el del cor, a travĂ©s de tres aplicacions: (i) estimaciĂł del moviment cardĂac per al diagnòstic, (ii) estimaciĂł de forces i (iii) predicciĂł del moviment, orientant-se les dues Ăşltimes en cirurgia robòtica.
En primer lloc, ens centrem en un tema principal en la imatge cardĂaca, que Ă©s l’estimaciĂł del moviment cardĂac. L’objectiu principal Ă©s oferir als metges mesures objectives i comprensibles per ajudar-los en el diagnòstic de les malalties cardiovasculars. Fem servir dades d’ultrasons ultrarĂ pids i eines per al moviment d’imatges procedents de diverses Ă rees, com ara l’anĂ lisi de baix rang i la deformaciĂł variacional, per fer una estimaciĂł realista del moviment cardĂac. La importĂ ncia rau en que, en prendre les dades de baix rang amb una penalitzaciĂł acurada, es poden crear sinergies en aquest problema variacional complex. Mitjançant acurats experiments numèrics, amb dades realĂstiques i simulades, hem demostrat com les nostres propostes solucionen deformacions complexes.
Després passem del diagnòstic a la cirurgia robòtica, on els cirurgians realitzen procediments delicats remotament, a través de manipuladors robòtics, sense interactuar directament amb els pacients. Com a conseqüència, no tenen la percepció de la força com a resposta, que és un sentit primari important per augmentar la transparència entre el cirurgià i el pacient, per evitar lesions i per
reduir la cĂ rrega de treball mental. Resolem aquest problema seguint els principis de conservaciĂł de la mecĂ nica del medi continu, en els quals estĂ clar que el canvi en la forma d’un objecte elĂ stic Ă©s directament proporcional a la força aplicada. Per això hem creat un marc variacional que adquireix la deformaciĂł que pateixen els teixits per l’aplicaciĂł d’una força. Aquesta informaciĂł s’utilitza en un sistema d’aprenentatge, per trobar la relaciĂł no lineal entre les dades donades i la força aplicada. Hem dut a terme experiments amb dades in-vivo i ex-vivo i hem combinat l’anĂ lisi estadĂstic, grĂ fic i de percepciĂł que demostren la robustesa de la nostra soluciĂł. Finalment, explorem la cirurgia cardĂaca robòtica, la qual cosa permet realitzar procediments complexos, incloent la cirurgia coronĂ ria sense bomba (off-pump coronary artery bypass grafting o OPCAB). Aquest procediment evita les complicacions associades a l’ús de circulaciĂł extracorpòria (Cardiopulmonary Bypass o CPB), ja que el cor no s’atura mentre es realitza la cirurgia. Això
comporta que els cirurgians han de tractar amb un objectiu dinà mic que compromet la seva destresa i la precisió de la cirurgia. Per compensar el moviment del cor, proposem una solució composta de tres elements: un funcional d’energia per estimar el moviment tridimensional del cor, una estratègia de detecció de les reflexions especulars i una aproximació basada en mètodes de predicció, per tal d’augmentar la robustesa de la solució. L’avaluació de la nostra solució s’ha dut
a terme mitjançant conjunts de dades sintètiques i realistes.
La tesi conclou informant dels nostres resultats en aquestes tres aplicacions i posant de relleu la dependència entre l’estimaciĂł i la comprensiĂł del moviment en qualsevol esdeveniment dinĂ mic, especialment en escenaris clĂnics.Postprint (published version
Deformable Prototypes for Encoding Shape Categories in Image Databases
We describe a method for shape-based image database search that uses deformable prototypes to represent categories. Rather than directly comparing a candidate shape with all shape entries in the database, shapes are compared in terms of the types of nonrigid deformations (differences) that relate them to a small subset of representative prototypes. To solve the shape correspondence and alignment problem, we employ the technique of modal matching, an information-preserving shape decomposition for matching, describing, and comparing shapes despite sensor variations and nonrigid deformations. In modal matching, shape is decomposed into an ordered basis of orthogonal principal components. We demonstrate the utility of this approach for shape comparison in 2-D image databases.Office of Naval Research (Young Investigator Award N00014-06-1-0661
A full Eulerian finite difference approach for solving fluid-structure coupling problems
A new simulation method for solving fluid-structure coupling problems has
been developed. All the basic equations are numerically solved on a fixed
Cartesian grid using a finite difference scheme. A volume-of-fluid formulation
(Hirt and Nichols (1981, J. Comput. Phys., 39, 201)), which has been widely
used for multiphase flow simulations, is applied to describing the
multi-component geometry. The temporal change in the solid deformation is
described in the Eulerian frame by updating a left Cauchy-Green deformation
tensor, which is used to express constitutive equations for nonlinear
Mooney-Rivlin materials. In this paper, various verifications and validations
of the present full Eulerian method, which solves the fluid and solid motions
on a fixed grid, are demonstrated, and the numerical accuracy involved in the
fluid-structure coupling problems is examined.Comment: 38 pages, 27 figures, accepted for publication in J. Comput. Phy
Doctor of Philosophy
dissertationDespite the progress that has been made since the inception of the finite element method, the field of biomechanics has generally relied on software tools that were not specifically designed to target this particular area of application. Software designed specifically for the field of computational biomechanics does not appear to exist. To overcome this limitation, FEBio was developed, an acronym for “Finite Elements for Biomechanics”, which provided an open-source framework for developing finite element software that is tailored to the specific needs of the biomechanics and biophysics communities. The proposed work added an extendible framework to FEBio that greatly facilitates the implementation of novel features and provides an ideal platform for exploring novel computational approaches. This framework supports plugins, which simplify the process of adding new features even more since plugins can be developed independently from the main source code. Using this new framework, this work extended FEBio in two important areas of interest in biomechanics. First, as tetrahedral elements continue to be the preferred modeling primitive for representing complex geometries, several tetrahedral formulations were investigated in terms of their robustness and accuracy for solving problems in computational biomechanics. The focus was on the performance of quadratic tetrahedral formulations in large deformation contact analyses, as this is an important area of application in biomechanics. Second, the application of prestrain to computational models has been recognized as an important component in simulations of biological tissues in order to accurately predict the mechanical response. As this remains challenging to do in existing software packages, a general computational framework for applying prestrain was incorporated in the FEBio software. The work demonstrated via several examples how plugins greatly simplify the development of novel features. In addition, it showed that the quadratic tetrahedral formulations studied in this work are viable alternatives for contact analyses. Finally, it demonstrated the newly developed prestrain plugin and showed how it can be used in various applications of prestrain
- …