About this Research Topic
Background. Medical simulation spans several areas where medicine converges with modeling and simulation (M&S). Computer-based medical simulation exploits computers to synthesize the response of tissues to therapy, which equates with a trade-off between computational efficiency and fidelity to tissue response. High-fidelity medical/surgical simulation is generally used to provide experienced clinicians, such as surgeons, with cues on optimizing treatment of the patient, while high-throughput simulation emphasizes real-time interactivity for haptics. Interactive medical simulation is typically used in conjunction with Virtual Reality (VR) visualization for skill acquisition and training.
Goal. In both cases, predictive and interactive simulation, a computer visualization of is needed, typically of the anatomy, though other views are possible, such as a representation of physiological processes. In the interactive VR context, this visualization must be also responsive in real-time, which presupposes highly efficient therapy models (e.g., interactive cutting) and relatively sparse anatomical models and collision models, which in turn determines where the therapy takes place, in conjunction with the position and orientation of the haptic device.
Scope. Related research areas include segmentation of medical images that convert intensities to tissue labels and meshing that discretize tissues into elements; efficiencies that enable high throughputs, such as acceleration based on specialized hardware, including GPUs and FPGAs, and deep convolutional/graph neural networks that use a learning process in order to simply complex behavior. These techniques can also be used for medical visualization in a novel exploratory sense, coupled with a static scene.
This Research Topic is dedicated to all areas of convergence between computer-assisted medicine, emphasizing simulation and visualization, including the use of segmentation and meshing needed to process medical images to produce vivid visualizations, neural networks and hardware efficiencies, as well as novel medical and hybrid applications that compellingly couple with computer visualization.
Goal. In both cases, predictive and interactive simulation, a computer visualization of is needed, typically of the anatomy, though other views are possible, such as a representation of physiological processes. In the interactive VR context, this visualization must be also responsive in real-time, which presupposes highly efficient therapy models (e.g., interactive cutting) and relatively sparse anatomical models and collision models, which in turn determines where the therapy takes place, in conjunction with the position and orientation of the haptic device.
Scope. Related research areas include segmentation of medical images that convert intensities to tissue labels and meshing that discretize tissues into elements; efficiencies that enable high throughputs, such as acceleration based on specialized hardware, including GPUs and FPGAs, and deep convolutional/graph neural networks that use a learning process in order to simply complex behavior. These techniques can also be used for medical visualization in a novel exploratory sense, coupled with a static scene.
This Research Topic is dedicated to all areas of convergence between computer-assisted medicine, emphasizing simulation and visualization, including the use of segmentation and meshing needed to process medical images to produce vivid visualizations, neural networks and hardware efficiencies, as well as novel medical and hybrid applications that compellingly couple with computer visualization.
Keywords: Medical Simulation, Medical Visualization, Haptics, Deep Neural Networks, Medical Image Segmentation, Meshing, Therapy Models, Hybrid Simulations
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