48,661 research outputs found
Soft tissue structure modelling for use in orthopaedic applications and musculoskeletal biomechanics
We present our methodology for the three-dimensional anatomical and geometrical description of soft tissues, relevant for orthopaedic surgical applications and musculoskeletal biomechanics. The technique involves the segmentation and geometrical description of muscles and neurovascular structures from high-resolution computer tomography scanning for the reconstruction of generic anatomical models. These models can be used for quantitative interpretation of anatomical and biomechanical aspects of different soft tissue structures. This approach should allow the use of these data in other application fields, such as musculoskeletal modelling, simulations for radiation therapy, and databases for use in minimally invasive, navigated and robotic surgery
Oriented tensor reconstruction: tracing neural pathways from diffusion tensor MRI
In this paper we develop a new technique for tracing anatomical fibers from 3D tensor fields. The technique extracts salient tensor features using a local regularization technique that allows the algorithm to cross noisy regions and bridge gaps in the data. We applied the method to human brain DT-MRI data and recovered identifiable anatomical structures that correspond to the white matter brain-fiber pathways. The images in this paper are derived from a dataset having 121x88x60 resolution. We were able to recover fibers with less than the voxel size resolution by applying the regularization technique, i.e., using a priori assumptions about fiber smoothness. The regularization procedure is done through a moving least squares filter directly incorporated in the tracing algorithm
Orbital and Maxillofacial Computer Aided Surgery: Patient-Specific Finite Element Models To Predict Surgical Outcomes
This paper addresses an important issue raised for the clinical relevance of
Computer-Assisted Surgical applications, namely the methodology used to
automatically build patient-specific Finite Element (FE) models of anatomical
structures. From this perspective, a method is proposed, based on a technique
called the Mesh-Matching method, followed by a process that corrects mesh
irregularities. The Mesh-Matching algorithm generates patient-specific volume
meshes from an existing generic model. The mesh regularization process is based
on the Jacobian matrix transform related to the FE reference element and the
current element. This method for generating patient-specific FE models is first
applied to Computer-Assisted maxillofacial surgery, and more precisely to the
FE elastic modelling of patient facial soft tissues. For each patient, the
planned bone osteotomies (mandible, maxilla, chin) are used as boundary
conditions to deform the FE face model, in order to predict the aesthetic
outcome of the surgery. Seven FE patient-specific models were successfully
generated by our method. For one patient, the prediction of the FE model is
qualitatively compared with the patient's post-operative appearance, measured
from a Computer Tomography scan. Then, our methodology is applied to
Computer-Assisted orbital surgery. It is, therefore, evaluated for the
generation of eleven patient-specific FE poroelastic models of the orbital soft
tissues. These models are used to predict the consequences of the surgical
decompression of the orbit. More precisely, an average law is extrapolated from
the simulations carried out for each patient model. This law links the size of
the osteotomy (i.e. the surgical gesture) and the backward displacement of the
eyeball (the consequence of the surgical gesture)
A fast and robust patient specific Finite Element mesh registration technique: application to 60 clinical cases
Finite Element mesh generation remains an important issue for patient
specific biomechanical modeling. While some techniques make automatic mesh
generation possible, in most cases, manual mesh generation is preferred for
better control over the sub-domain representation, element type, layout and
refinement that it provides. Yet, this option is time consuming and not suited
for intraoperative situations where model generation and computation time is
critical. To overcome this problem we propose a fast and automatic mesh
generation technique based on the elastic registration of a generic mesh to the
specific target organ in conjunction with element regularity and quality
correction. This Mesh-Match-and-Repair (MMRep) approach combines control over
the mesh structure along with fast and robust meshing capabilities, even in
situations where only partial organ geometry is available. The technique was
successfully tested on a database of 5 pre-operatively acquired complete femora
CT scans, 5 femoral heads partially digitized at intraoperative stage, and 50
CT volumes of patients' heads. The MMRep algorithm succeeded in all 60 cases,
yielding for each patient a hex-dominant, Atlas based, Finite Element mesh with
submillimetric surface representation accuracy, directly exploitable within a
commercial FE software
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