Bleeding simulation with stepless adaptive particles for surgical simulation systems.

Background And Objectives: In virtual surgery, the resolution of bleeding surface has a significant impact on the realism. The computational complexity of internal particles reduces real-time performance, which has no obvious contribution to the visual effect of simulation. This paper focuses on the study of bleeding simulation in virtual surgery to improve the visual realism while meeting real-time performance and physical properties.

Simulation of soft tissue deformation under physiological motion based on complementary dynamic method.

Background And Objective: Physiological motions have a significant impact on soft tissue deformation and accuracy of surgical procedures, which is essential for realistic surgical simulation. While existing studies offer accurate simulation of soft tissue deformation, integrating physiological motions into deformation models of soft tissue remains a challenging task.

Methods: This paper introduces a novel deformation model, based on complementary dynamics, to animate soft tissue deformation under physiological motion.

Modeling fibrous soft tissue dissection with elastic-plastic deformation for simulation of brain tumor removal.

Background And Objective: Realistic modeling the dissection of brain tissue is of key importance for simulation of brain tumor removal in virtual neurosurgery systems. However, existing methods are unable to characterize inelastic behaviors of brain tissue, such as plastic deformation and dissection evolution, making it ineffective in simulating brain tumor removal procedures.

Methods: In this paper, a model of fibrous soft tissue dissection for the simulation of brain tumor removal is proposed.

Fully automated cardiac MRI segmentation using dilated residual network.

Purpose: Cardiac ventricle segmentation from cine magnetic resonance imaging (CMRI) is a recognized modality for the noninvasive assessment of cardiovascular pathologies. Deep learning based algorithms achieved state-of-the-art result performance from CMRI cardiac ventricle segmentation. However, most approaches received less attention at the bottom layer of UNet, where main features are lost due to pixel degradation.

Modeling of glioma growth using modified reaction-diffusion equation on brain MR images.

Background And Objective: Modeling of glioma growth and evolution is of key importance for cancer diagnosis, predicting clinical progression and improving treatment outcomes of neurosurgery. However, existing models are unable to characterize spatial variations of the proliferation and infiltration of tumor cells, making it difficult to achieve accurate prediction of tumor growth.

Methods: In this paper, a new growth model of brain tumor using a reaction-diffusion equation on brain magnetic resonance images is proposed.

A deformation model of pulsating brain tissue for neurosurgery simulation.

Background And Objectives: For neurological simulation, an accurate deformation model of brain tissue is of key importance for faithful visual feedback. Existing models, however, do not take into account intracranial pulsation, which degrades significantly the realism of visual feedback.

Methods: In this paper, a finite element model incorporating intracranial pressure is proposed for simulating brain tissue deformation with pulsation.

Modeling of connective tissue damage for blunt dissection of brain tumor in neurosurgery simulation.

We introduce a new model for connective tissue damage in blunt dissection, which is a very important process in neurosurgery simulation. Specifically, the tool-tissue interaction between the instrument and connective tissue is incorporated into the model of connective tissue damage. This damage develops with the evolution criterion due to the effect of the external load.

A new model of soft tissue with constraints for interactive surgical simulation.

Background And Objectives: An accurate and real-time model of soft tissue is critical for surgical simulation for which a user interacts haptically and visually with simulated patients. This paper focuses on the real-time deformation model of brain tissue for the interactive surgical simulation, such as neurosurgical simulation.

Methods: A new Finite Element Method (FEM) based model with constraints is proposed for the brain tissue in neurosurgical simulation.