Real-Time Voxel-based 2D to 3D CT Visualisation Framework for Volumetric Capacity Estimation
Over the decades medical analyses have grown in importance and practice possibilities. Digital operations like split-image procedures have become an integral part of modern medical practices and are still gaining momentum. Through the application of this technique medical computed tomography (CT) and magnetic resonance imaging scans (MRI) can be converted to three-dimensional bodies. This paper intends to use these generated objects in a process called segmentation. During this procedure, the desired area gets separated from the rest of the body for analysis and calculation of its physical properties. Furthermore, segmentation can be greatly improved through the utilization of algorithms such as U-Net and K-means or features like augmented reality (AR) or virtual reality (VR). The goal of this paper is to provide doctors with a reliable and simple to use program, which greatly aides in the analysis of patients’ data.
CitationA. Schuchter, G. Petrarolo and D. Grießner, "Real-Time Voxel-based 2D to 3D CT Visualisation Framework for Volumetric Capacity Estimation," 2022 E-Health and Bioengineering Conference (EHB), Iasi, Romania, 2022.
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