A Novel Compression-Driven Lightweight Framework for Medical Skeleton Model Visualization - Wen Zhou; Jinyuan Jia; Xin Su (IEEE Access, 2018)
In the field of medical imaging, many medical image data can be rebuilt into 3-D medical models for use in medical education and analysis. In fact, the 3-D medical models help ordinary people (including patients and students) to more easily understand and learn medical knowledge. In addition, with the rapid development of Web3D technology, the demand for 3-D visualization technology based on the web browser increases. However, the limited bandwidth and low load capacity of the browser have seriously restricted the development of technology. Therefore, this paper proposes a framework to better show 3-D skeleton shapes. In particular, mesh compression is one of the most effective methods to achieve a fast transmission data process. In addition, because of the poor rendering capabilities of the browsers, it is notably difficult to render the entire model at once. Moreover, it often makes the browser crash; thus, the transmitted model data are only rendered once. In addition, a mesh segmentation algorithm is proposed to realize component-wise rendering and lightweight for shape. A voxel-based component repetition method is used to detect the repetitive components; thus, we can perform matrix transformation to finish the repetitive-component Web3D visualization, i.e., lightweight for shape. Finally, the related experiments are performed to validate our proposed framework. The results show that the proposed framework is feasible and superior.