AIMC Topic: Finite Element Analysis

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A machine learning approach for real-time modelling of tissue deformation in image-guided neurosurgery.

Artificial intelligence in medicine
OBJECTIVES: Accurate reconstruction and visualisation of soft tissue deformation in real time is crucial in image-guided surgery, particularly in augmented reality (AR) applications. Current deformation models are characterised by a trade-off between...

Continuous uniformly finite time exact disturbance observer based control for fixed-time stabilization of nonlinear systems with mismatched disturbances.

PloS one
This paper presents a continuous composite control scheme to achieve fixed-time stabilization for nonlinear systems with mismatched disturbances. The composite controller is constructed in two steps: First, uniformly finite time exact disturbance obs...

A machine learning approach to investigate the relationship between shape features and numerically predicted risk of ascending aortic aneurysm.

Biomechanics and modeling in mechanobiology
Geometric features of the aorta are linked to patient risk of rupture in the clinical decision to electively repair an ascending aortic aneurysm (AsAA). Previous approaches have focused on relationship between intuitive geometric features (e.g., diam...

Development of an in vivo visual robot system with a magnetic anchoring mechanism and a lens cleaning mechanism for laparoendoscopic single-site surgery (LESS).

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Surgical robot systems which can significantly improve surgical procedures have been widely used in laparoendoscopic single-site surgery (LESS). For a relative complex surgical procedure, the development of an in vivo visual robot system ...

Machine Learning Approach for Predicting Wall Shear Distribution for Abdominal Aortic Aneurysm and Carotid Bifurcation Models.

IEEE journal of biomedical and health informatics
Computer simulations based on the finite element method represent powerful tools for modeling blood flow through arteries. However, due to its computational complexity, this approach may be inappropriate when results are needed quickly. In order to r...

An information-based machine learning approach to elasticity imaging.

Biomechanics and modeling in mechanobiology
An information-based technique is described for applications in mechanical property imaging of soft biological media under quasi-static loads. We adapted the Autoprogressive method that was originally developed for civil engineering applications for ...

Biomechanical advantages of robot-assisted pedicle screw fixation in posterior lumbar interbody fusion compared with freehand technique in a prospective randomized controlled trial-perspective for patient-specific finite element analysis.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: There have been conflicting results on the surgical outcome of lumbar fusion surgery using two different techniques: robot-assisted pedicle screw fixation and conventional freehand technique. In addition, there have been no studie...

Methodology for designing and manufacturing complex biologically inspired soft robotic fluidic actuators: prosthetic hand case study.

Bioinspiration & biomimetics
We present a novel methodology for the design and manufacture of complex biologically inspired soft robotic fluidic actuators. The methodology is applied to the design and manufacture of a prosthetic for the hand. Real human hands are scanned to prod...

Machine learning-based 3-D geometry reconstruction and modeling of aortic valve deformation using 3-D computed tomography images.

International journal for numerical methods in biomedical engineering
To conduct a patient-specific computational modeling of the aortic valve, 3-D aortic valve anatomic geometries of an individual patient need to be reconstructed from clinical 3-D cardiac images. Currently, most of computational studies involve manual...

Uncertainty Quantification of Oscillation Suppression During DBS in a Coupled Finite Element and Network Model.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Models of the cortico-basal ganglia network and volume conductor models of the brain can provide insight into the mechanisms of action of deep brain stimulation (DBS). In this study, the coupling of a network model, under parkinsonian conditions, to ...