Visualization of Medical Images Data Based on Geometric Modeling

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Abstract

The methods for visualizing data are considered as the graphical representation of information and data. These data are first analyzed and computed depending on the criteria and purpose of users. Thereafter, they are visualized or simulated by using visual elements like charts, graphs and maps to explore, understand their characteristics and data structure. In the studies of big data analysis or data science, the methods, tools and techniques are essential and important to analyze a massive amount of information and make data-driven decisions. Which methods or solutions are best for rendering and visualizing the analyzed data? That is still a big question; even a challenge to the researchers. In this paper, we research and implement a web-based application for visualizing the medical images data based on geometric modeling. After studying the state-of-the-art in the fields of computer graphics, images processing and geometric modeling, we combine all of them to develop an application for rendering the Dicom data. The input data are slices of 2D of an object captured from CT scanner or MRI. They are processed and reconstructed for rendering its initial shape on both 2D and 3D environment. Comparing to the existing applications, our research shown the advantages of using it in practice.

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Nguyen, V. S., Tran, M. H., & Le, S. T. (2019). Visualization of Medical Images Data Based on Geometric Modeling. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11814 LNCS, pp. 560–576). Springer. https://doi.org/10.1007/978-3-030-35653-8_36

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