Biomedical subjects

Jesper Mosegaard

Publications and source records attributed to Jesper Mosegaard.

4 recordsLinked to original sources

PubMed2006

Haptic feedback for the GPU-based surgical simulator.

The GPU has proven to be a powerful processor to compute spring-mass based surgical simulations. It has not previously been shown however, how to effectively implement haptic interaction with a simulation running entirely on the GPU. This paper describes a method to calculate haptic feedback with limited performance cost. It allows easy balancing of the GPU workload between calculations of simulation, visualisation, and the haptic feedback.

Computer Graphics↗

PubMed2005

A GPU accelerated spring mass system for surgical simulation.

There is a growing demand for surgical simulators to do fast and precise calculations of tissue deformation to simulate increasingly complex morphology in real-time. Unfortunately, even fast spring-mass based systems have slow convergence rates for large models. This paper presents a method to accelerate computation of a spring-mass system in order to simulate a complex organ such as the heart. This acceleration is achieved by taking advantage of modern graphics processing units (GPU).

Computer Simulation↗

PubMed2004

Parameter optimisation for the behaviour of elastic models over time.

Optimisation of parameters for elastic models is essential for comparison or finding equivalent behaviour of elastic models when parameters cannot simply be transferred or converted. This is the case with a large range of commonly used elastic models. In this paper we present a general method that will optimise parameters based on the behaviour of the elastic models over time.

Algorithms↗

PubMed2004

LR-Spring Mass model for cardiac surgical simulation.

The purpose of the research conducted was to develop a real-time surgical simulator for preoperative planning of surgery in congenital heart disease. The main problem simulating procedures on cardiac morphology is the need for a large degree of detail and simulation speed. In combination with a demand for physically realistic real-time behaviour this gives us tradeoffs not easily balanced. The LR-Spring Mass model handles these constraints by the use of domain specific knowledge.

Algorithms↗