Processing and 3D printing of Gradient Heterogeneous Bio-Model Based on Computer Tomography Images

Li, Zongan; Yang, Jiquan; Wang, Qiong; Shi, Jianping; Zhu, Linli; Xu, Rongjian; Li, Kelou; Tang, Wencheng

doi:10.1109/access.2016.2635661

Cited by 11 publications

(2 citation statements)

References 29 publications

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“…The obtained result of a 3D medical model is then used for 3D printer. Zonggan et al [30] proposed a method for processing and printing the 3D objects of biomodels based on a medical dataset from computer tomography images. The method is developed by analyzing geometrical features of a 3D object.…”

Section: Current Researchesmentioning

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: Current Researchesmentioning

confidence: 99%

Application of Geometric Modeling in Visualizing the Medical Image Dataset

Nguyen

Tran

2020

SN COMPUT. SCI.

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“…Introduction: 3D printing, also known as additive manufacturing process, gained wide prominence in prototyping markets and customised products due to its simplicity in reproducing a computer-aided design model [1,2]. Nowadays, the usage of 3D printing is extended to electronics [2], medical and dental prostheses [3,4]. Quite recently, it has been demonstrated that this technology could also be used to produce smart-materials, i.e.…”

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confidence: 99%

Hydrophone based on 3D printed polypropylene (PP) piezoelectret

et al. 2019

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Every year, different areas of knowledge are becoming more interested in 3D-printing technology. Recently, this technology was also proved to be feasible for creating sensitive materials such as piezoelectrets. This Letter extends the concept of a 3D printed piezoelectret to produce a pressure sensitive film that can be employed as an ultrasonic transducer for underwater applications, such as hydrophones. In order to achieve this, a two-layer polypropylene film was printed using a filament-based 3D printer. Afterwards, adhesive electrodes were attached on both sides of the film and electrical charging was applied. Later, the 3D printed film was mounted in a metal housing specially designed to keep the film in direct contact with the water and to isolate the electronic amplification. The validation was performed using a piezoelectric ceramic made of lead zirconate titanate (PZT), immersed in a water tank, to produce ultrasonic sweeps to be sensed by the 3D printed transducer. These tests revealed sensor sensitivities up to 600 mV and promote a precise detection of the acoustic resonance frequency of the PZT at 43.7 kHz.

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