Filling Hole on the Surface of 3D Point Clouds Based on Reverse Computation of Bezier Curves

Nguyen, Van Sinh; Tran, Khai Minh; Tran, Ha Manh

doi:10.1007/978-981-10-7512-4_34

Cited by 7 publications

(1 citation statement)

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“…Starting to work in the geometrical features (such as points, lines, triangles, faces, curves, surfaces, etc.) to process and handle a 2D or a 3D object, we proposed a list of methods for each of these processing in the previous work [7][8][9]. These methods are used to process the 3D objects from a 3D point cloud.…”

Section: Introductionmentioning

confidence: 99%

Application of Geometric Modeling in Visualizing the Medical Image Dataset

Nguyen

Tran

2020

SN COMPUT. SCI.

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Geometric modeling is a research based on computational geometry for processing the 3D objects in computer graphics or image processing. Rendering the graphical objects in medical applications is an interesting research that can help doctors have an exact decision in their diagnostic method. Application of geometric modeling in visualization of medical data is considered as a tool to support treatment. In the field of big data analysis and data science, the methods, tools and techniques are essential and important to analyze a massive amount of information and make data-driven decisions. These data are first analyzed and computed depending on the criteria and purpose of users. They are then visualized or simulated using visual elements like charts, graphs or maps to explore, understand their characteristics and data structure. Which method or solution is best for rendering and visualizing the analyzed data? That is still a question and even a challenge to the researchers. In this article, we apply geometric modeling to build a web-based application for visualizing a medical image dataset. This is an improved version of the selected paper in the previous work[1]. We first review several researches in the fields of computer graphics, images processing, geometric modeling and their applications; then we combine all of them and propose a method to develop our application for reconstructing the medical data objects. The input data are a Dicom (Digital Imaging and Communications in Medicine) dataset captured from CT (computed tomography) scanner or MRI (Magnetic Resonance Imaging). The output are 2D and 3D models that can be displayed and handled in different ways on the web interface. In comparison with other existing applications, our method shown the advantages of its using in practice.

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Section: Introductionmentioning

confidence: 99%