Application of soft tissue modelling to image-guided surgery

Carter, Timothy J.; Sermesant, Maxime; Cash, David M.; Barratt, Dean C.; Tanner, Christine; Hawkes, David J.

doi:10.1016/j.medengphy.2005.10.005

Cited by 97 publications

(57 citation statements)

References 95 publications

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“…While the technique is presently reliant on an initial registration estimate, the average capture range required for convergence ͑found to be 5.9 mm in translation and 5.2 deg in rotation͒ encompasses the accuracy obtained with point-based fiducial registration as typically practiced in the OR. The automated and computationally efficient ͑average execution time of 1 min͒ character of the approach makes it attractive for effective use of coregistered iUS in the OR for brain shift compensation, either as a stand-alone navigational aid [38][39][40] or in concert with other techniques ͑e.g., brain deformation modeling [41][42][43] ͒ for intraoperative image guidance. This scheme also holds promise for eliminating the reliance on more laborious fiducial-based registration.…”

Section: Discussionmentioning

confidence: 99%

Mutual‐information‐based image to patient re‐registration using intraoperative ultrasound in image‐guided neurosurgery

Hartov

et al. 2008

Medical Physics

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An image-based re-registration scheme has been developed and evaluated that uses fiducial registration as a starting point to maximize the normalized mutual information ͑nMI͒ between intraoperative ultrasound ͑iUS͒ and preoperative magnetic resonance images ͑pMR͒. We show that this scheme significantly ͑p Ӷ 0.001͒ reduces tumor boundary misalignment between iUS pre-durotomy and pMR from an average of 2.5 mm to 1.0 mm in six resection surgeries. The corrected tumor alignment before dural opening provides a more accurate reference for assessing subsequent intraoperative tumor displacement, which is important for brain shift compensation as surgery progresses. In addition, we report the translational and rotational capture ranges necessary for successful convergence of the nMI registration technique ͑5.9 mm and 5.2 deg, respectively͒. The proposed scheme is automatic, sufficiently robust, and computationally efficient ͑Ͻ2 min͒, and holds promise for routine clinical use in the operating room during image-guided neurosurgical procedures.

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Section: Discussionmentioning

confidence: 99%

Mutual‐information‐based image to patient re‐registration using intraoperative ultrasound in image‐guided neurosurgery

Hartov

et al. 2008

Medical Physics

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“…The choice of linear tetrahedral elements allowed the computation of analytical integrands, facilitating the meshing of the structures [68] since a smaller number of elements is required to obtain a smooth surface. Some authors [55], [57] claim that hexahedral or higher order elements are needed to avoid locking effects and to permit the computation of large displacements, when modelling almost incompressible material.…”

Section: Discussionmentioning

confidence: 99%

“…For the Poisson's ratio, we have chosen a value of 0.45 for each brain tissue. Even if the human brain is expected to be more incompressible than that, it has been shown that the choice of an appropriate set of boundary conditions is more critical than the exact value of the material properties [68]. Using (2) and the values of the Poisson's ratio and the shear modulus stated above, we obtain a Young's modulus of 34.8 kPa for the white matter and 23.2 kPa for the grey matter.…”

Section: B Boundary Conditions and Mechanical Properties Of Brain Timentioning

confidence: 96%

Phenomenological Model of Diffuse Global and Regional Atrophy Using Finite-Element Methods

Cámara

Schweiger

Scahill

et al. 2006

IEEE Trans. Med. Imaging

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Abstract-The main goal of this work is the generation of ground-truth data for the validation of atrophy measurement techniques, commonly used in the study of neurodegenerative diseases such as dementia. Several techniques have been used to measure atrophy in cross-sectional and longitudinal studies, but it is extremely difficult to compare their performance since they have been applied to different patient populations. Furthermore, assessment of performance based on phantom measurements or simple scaled images overestimates these techniques' ability to capture the complexity of neurodegeneration of the human brain. We propose a method for atrophy simulation in structural magnetic resonance (

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“…fluid elastic models, allow for the assignment of different elasticity factors for different regions of an organ in order to model for instance a tumor. A technical elaborative survey about biomechanical modeling for image-guided surgery is given by Carter et al [11].…”

Section: Organ Shift and Tissue Deformationmentioning

confidence: 99%

Navigation in Endoscopic Soft Tissue Surgery: Perspectives and Limitations

Baumhauer

Feuerstein

Meinzer

et al. 2008

Journal of Endourology

163

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Abstract-Despite rapid developments in the research areas medical imaging, medical image processing and robotics, the use of computer assistance in surgical routine is still limited to diagnostics, surgical planning, and interventions on mostly rigid structures. In order to establish a computer aided workflow from diagnosis to surgical treatment and follow-up, several proposals for computer assisted soft tissue interventions have been made in recent years. By means of different pre-and intraoperative information sources, like surgical plannings, intraoperative imaging, and tracking devices, surgical navigation systems aim at supporting surgeons in localizing anatomical targets, observing critical structures, and sparing healthy tissue. Current research in particular addresses the problem of organ shift and tissue deformation, and obstacles in communication between navigation system and surgeon.In this article, we review computer assisted navigation systems for soft tissue surgery. We concentrate on approaches which can be applied in endoscopic thoracic and abdominal surgery, as endoscopic surgery has special needs for image guidance due to limitations in perception. Furthermore, this article provides the reader with new trends and technologies in the area of computer assisted surgery. Finally, a balancing of key challenges and possible benefits of endoscopic navigation refines the perspectives of this increasingly important discipline of computer aided medical procedures.

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Application of soft tissue modelling to image-guided surgery

Cited by 97 publications

References 95 publications

Mutual‐information‐based image to patient re‐registration using intraoperative ultrasound in image‐guided neurosurgery

Mutual‐information‐based image to patient re‐registration using intraoperative ultrasound in image‐guided neurosurgery

Phenomenological Model of Diffuse Global and Regional Atrophy Using Finite-Element Methods

Navigation in Endoscopic Soft Tissue Surgery: Perspectives and Limitations

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