Real-time haptic incision simulation using FEM-based discontinuous free-form deformation

Sela, Guy; Subag, Jacob; Alex, Lindblad,; Albocher, Dan; Schein, Sagi; Elber, Gershon

doi:10.1016/j.cad.2007.05.011

Cited by 30 publications

(11 citation statements)

References 7 publications

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“…Equation [18] is updated once for each time step, in which the cursor at the point in contact with the surface is changed manually, hence becoming u tþ1 .…”

Section: Displacement Updatementioning

confidence: 99%

Haptic interaction of organs based on the spherical harmonic representation

Yang

Vegh

Tieng

et al. 2010

Concepts Magn Reson

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Visual and haptic organ interactions in real time are essential in virtual reality-based medical simulations to provide training, early diagnosis, and improved treatment planning. This work presents a robust method of computing the deformation of an elastic object when external forces are applied. Point-based haptic interaction between the user of the haptic device and an object is outlined and is formulated as a deformation problem over the surface. The model is expressed in the spherical harmonic basis, from which both haptic device force feedback and object surface updates are calculated. Haptic and visual updates are performed in the same basis, in turn providing significant benefits of computing efficiency and multiresolution modeling. Partially, this is due to the fact that in the model the objects are represented as surfaces. A haptic device is used to probe different prostates that have been segmented and reconstructed from MR images to validate the findings. The calculated deformation and feedback force is further validated against the established finite element method.

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“…Equation [18] is updated once for each time step, in which the cursor at the point in contact with the surface is changed manually, hence becoming u tþ1 .…”

Section: Displacement Updatementioning

confidence: 99%

Haptic interaction of organs based on the spherical harmonic representation

Yang

Vegh

Tieng

et al. 2010

Concepts Magn Reson

View full text Add to dashboard Cite

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“…Linear FEM is used in the studies [Frank et al 2001;Mor and Kanade 2000;Nienhuys and van der Stappen 2000;Lindblad and Turkiyyah 2007;Sela et al 2007;Wu and Heng 2005]. In [Sela et al 2007], FEM calculations are done offline during the preprocessing step to evaluate constraints to simulate tissue cutting, then the constraints for the nodes along the cutting path are moved and the model is updated by using discontinuous discrete free form deformations during the simulation.…”

Section: Related Workmentioning

confidence: 99%

“…In [Sela et al 2007], FEM calculations are done offline during the preprocessing step to evaluate constraints to simulate tissue cutting, then the constraints for the nodes along the cutting path are moved and the model is updated by using discontinuous discrete free form deformations during the simulation. In [Wu and Heng 2005] modification of the tissue cutting was permitted but to achieve this the possible operation area is restricted to a local region in the prepocessing step.…”

Section: Related Workmentioning

confidence: 99%

Dynamic deformation using adaptable, linked asynchronous FEM regions

Koçak

Palmerius

Cooper

2009

Proceedings of the 25th Spring Conference on Computer Graphics

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In order to simulate both physically and visually realistic soft tissue deformations, the Finite Element Method (FEM) is the most popular choice in the literature. However it is non-trivial to model complex behaviour of soft tissue with sufficient refresh rates, especially for haptic force feedback which requires an update rate of the order of 1 kHz. In this study the use of asynchronous regions is proposed to speed up the solution of FEM equations in real-time. In this way it is possible to solve the local neighborhood of the contact with high refresh rates, while evaluating the more distant regions at lower frequencies, saving computational power to model complex behaviour within the contact area. Solution of the different regions using different methods is also possible. To attain maximum efficiency the size of the regions can be changed, in real-time, in response to the size of the deformation.

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“…To solve the problem, the large dataset is partitioned into several small sub-datasets, and the simulator is constructed by multiple networks, each of which is trained by using its corresponding sub-dataset. When external forces caused by surgical instruments are used as input data of the simulator, the approximation or the imitation of the FEM simulation may be achieved by using mass-spring model [90] and FreeForm Deformation (FFD) [91]. In this case, the parameters in the mass-spring and FFD models are adjusted by fitting the deformations of these models to the FEM simulations used as training data.…”

Section: Other Soft Tissuesmentioning

confidence: 99%

A Survey on Statistical Modeling and Machine Learning Approaches to Computer Assisted Medical Intervention: Intraoperative Anatomy Modeling and Optimization of Interventional Procedures

Morooka

Nakamoto

Sato

2013

IEICE Trans. Inf. & Syst.

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SUMMARYThis paper reviews methods for computer assisted medical intervention using statistical models and machine learning technologies, which would be particularly useful for representing prior information of anatomical shape, motion, and deformation to extrapolate intraoperative sparse data as well as surgeons' expertise and pathology to optimize interventions. Firstly, we present a review of methods for recovery of static anatomical structures by only using intraoperative data without any preoperative patient-specific information. Then, methods for recovery of intraoperative motion and deformation are reviewed by combining intraoperative sparse data with preoperative patient-specific stationary data, which is followed by a survey of articles which incorporated biomechanics. Furthermore, the articles are reviewed which addressed the used of statistical models for optimization of interventions. Finally, we conclude the survey by describing the future perspective.

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Real-time haptic incision simulation using FEM-based discontinuous free-form deformation

Cited by 30 publications

References 7 publications

Haptic interaction of organs based on the spherical harmonic representation

Haptic interaction of organs based on the spherical harmonic representation

Dynamic deformation using adaptable, linked asynchronous FEM regions

A Survey on Statistical Modeling and Machine Learning Approaches to Computer Assisted Medical Intervention: Intraoperative Anatomy Modeling and Optimization of Interventional Procedures

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