Real-time hybrid cutting with dynamic fluid visualization for virtual surgery

It is widely accepted that a reform in medical teaching must be made to meet today's high volume training requirements. Virtual simulation offers a potential method of providing such trainings and some current medical training simulations integrate haptic and visual feedback to enhance procedure learning. The purpose of this project is to explore the capability of Virtual Reality (VR) technology to develop a training simulator for surgical cutting and bleeding in a general surgery

Data-driven modelling of biological multi-scale processes

Biological processes involve a variety of spatial and temporal scales. A holistic understanding of many biological processes therefore requires multi-scale models which capture the relevant properties on all these scales. In this manuscript we review mathematical modelling approaches used to describe the individual spatial scales and how they are integrated into holistic models. We discuss the relation between spatial and temporal scales and the implication of that on multi-scale modelling. Based upon this overview over state-of-the-art modelling approaches, we formulate key challenges in mathematical and computational modelling of biological multi-scale and multi-physics processes. In particular, we considered the availability of analysis tools for multi-scale models and model-based multi-scale data integration. We provide a compact review of methods for model-based data integration and model-based hypothesis testing. Furthermore, novel approaches and recent trends are discussed, including computation time reduction using reduced order and surrogate models, which contribute to the solution of inference problems. We conclude the manuscript by providing a few ideas for the development of tailored multi-scale inference methods.Comment: This manuscript will appear in the Journal of Coupled Systems and Multiscale Dynamics (American Scientific Publishers

Cellular Automata

Modelling and simulation are disciplines of major importance for science and engineering. There is no science without models, and simulation has nowadays become a very useful tool, sometimes unavoidable, for development of both science and engineering. The main attractive feature of cellular automata is that, in spite of their conceptual simplicity which allows an easiness of implementation for computer simulation, as a detailed and complete mathematical analysis in principle, they are able to exhibit a wide variety of amazingly complex behaviour. This feature of cellular automata has attracted the researchers' attention from a wide variety of divergent fields of the exact disciplines of science and engineering, but also of the social sciences, and sometimes beyond. The collective complex behaviour of numerous systems, which emerge from the interaction of a multitude of simple individuals, is being conveniently modelled and simulated with cellular automata for very different purposes. In this book, a number of innovative applications of cellular automata models in the fields of Quantum Computing, Materials Science, Cryptography and Coding, and Robotics and Image Processing are presented

Computational Modelling of Cancer Systems: From Individual to Collective Cell Behaviour

Debido a su complejidad, el cáncer sigue siendo una de las principales causas de muerte a nivel mundial. La creación de prácticas preventivas adecuadas y terapias innovadoras está limitada por la falta de comprensión de los mecanismos básicos que causan el cáncer. Como tal, se deben desarrollar métodos nuevos y más efectivos que avancen nuestra comprensión del cáncer. En los últimos años, se ha visto un aumento en el uso de modelos computacionales para explicar procesos biológicos que son costosos y difíciles de explorar en entornos experimentales. Estos métodos permiten la traducción de mecanismos biológicos en ecuaciones y suposiciones matemáticas que pueden evaluarse utilizando herramientas informáticas para producir nuevas hipótesis. Además, las tecnologías computacionales se están volviendo más potentes debido a la disponibilidad de datos y la amplia capacidad de procesamiento.El objetivo global de esta tesis es diseñar e implementar modelos computacionales de cáncer, comenzando con comportamientos simples y aislados y progresando hacia fenómenos más complejos. Se abordan tres campos de investigación específicos para lograr este objetivo general: (i) motilidad unicelular, (ii) crecimiento tumoral y (iii) formación de patrones. En el primer objetivo, se presenta un modelo computacional para simular la motilidad celular individual que considera las propiedades mecánicas y químicas del microambiente. Posteriormente, este trabajo fue ampliado para tener en cuenta las interacciones célula-célula y reproducir el crecimiento de estructuras tumorales multicelulares. Por último, todos los eventos biológicos mencionados anteriormente fueron considerados y se añadió la diferenciación celular como el bloque de construcción final de esta tesis para simular la formación de patrones espaciales.Además, esta tesis analiza la relevancia de integrar datos experimentales y métodos computacionales para mejorar la precisión biológica y confirmar los resultados del modelo. En particular, muestra cómo se pueden usar técnicas de calibración y optimización para considerar datos empíricos en el diseño y validación de modelos. Los resultados experimentales cualitativos y cuantitativos, tanto de la literatura como de nuevos experimentos, se reproducen en este artículo para mostrar diferentes enfoques en la integración de datos.En general, esta tesis proporciona un modelo de cómo se pueden utilizar los métodos computacionales para analizar y comprender problemas complejos en la biología del cáncer.Demuestra explícitamente cómo los componentes del modelo pueden representar ciertos aspectos de la biología del cáncer, que pueden mejorarse y reproducirse utilizando datos experimentales. En consecuencia, los comportamientos complejos, como el crecimiento tumoral y la formación de patrones, resultan de la intrincada interacción entre los componentes del modelo.<br /

Realistic natural atmospheric phenomena and weather effects for interactive virtual environments.

Clouds and the weather are important aspects of any natural outdoor scene, but existing dynamic techniques within computer graphics only offer the simplest of cloud representations. The problem that this work looks to address is how to provide a means of simulating clouds and weather features such as precipitation, that are suitable for virtual environments. Techniques for cloud simulation are available within the area of meteorology, but numerical weather prediction systems are computationally expensive, give more numerical accuracy than we require for graphics and are restricted to the laws of physics. Within computer graphics, we often need to direct and adjust physical features or to bend reality to meet artistic goals, which is a key difference between the subjects of computer graphics and physical science. Pure physicallybased simulations, however, evolve their solutions according to pre-set rules and are notoriously difficult to control. The challenge then is for the solution to be computationally lightweight and able to be directed in some measure while at the same time producing believable results. This work presents a lightweight physically-based cloud simulation scheme that simulates the dynamic properties of cloud formation and weather effects. The system simulates water vapour, cloud water, cloud ice, rain, snow and hail. The water model incorporates control parameters and the cloud model uses an arbitrary vertical temperature profile, with a tool described to allow the user to define this. The result of this work is that clouds can now be simulated in near real-time complete with precipitation. The temperature profile and tool then provide a means of directing the resulting formation