Abstract. Mass-spring systems are of special interest for soft tissue modeling in surgical simulation due to their ease of implementation and real-time behavior. However, the parameter identification (masses, spring constants, mesh topology) still remains a challenge. In previous work, we proposed an approach based on the training of mass-spring systems according to known reference models. Our initial focus was the determination of mesh topology in 2D. In this paper, we extend the method to 3D. Furthermore, we introduce a new approach to simultaneously identify mesh topology and spring stiffness values. Linear elastic FEM deformation computations are used as reference. Additionally, our results show that uniform distributions of spring stiffness constants fails to simulate linear elastic deformations.

In our current research we examine the application of visuo-haptic augmented reality setups in medical training. To this end, highly accurate calibration, system stability, and low latency are indispensable prerequisites. These are necessary to maintain user immersion and avoid breaks in presence which potentially diminish the training outcome. In this paper we describe the developed calibration methods for visuo-haptic integration, the hybrid tracking technique for stable alignment of the augmentation, and the distributed framework ensuring low latency and component synchronization. Finally, we outline an early prototype system based on the multimodal augmented reality framework. The latter allows colocated visuo-haptic interaction with real and virtual scene components in a simplified open surgery setting.

Abstract. In surgical simulations, the two most popular approaches to model soft tissues are Finite Element Method (FEM) and Mass-Spring System (MSS). Main advantages of FEM are accuracy and realism. Furthermore, the model allows the direct integration of experimentally obtained biomechanical tissue parameters. However, computation times remain high, limiting real-time application of the method. In contrast to this, the main advantage of MSS is low computational complexity and simple implementation. These factors make the latter method highly attractive for virtual reality based surgical simulators. However, the specification of system parameters for a MSS (masses, spring constants, mesh topology) is not straightforward and remains a major difficulty of the approach. In this paper, we propose a solution to this problem based on evolutionary algorithms -our current focus being the determination of mesh topology. We use reference models to obtain the topology of a MSS. First results demonstrate, that the exact recovery of isotropic and anisotropic reference mesh configurations is possible.

A key is provided for the recognition of the hymenopterous parasitoids of the African white rice borer, Maliarpha separatella Ragonot, a pest of rice in Africa and Madagascar. Risbec. The known distributions, biologies and alternative hosts of each parasitoid are provided, and their use as biological control agents or components of integrated pest management programmes are discussed.