基于多探测器计算机断层扫描图像的牙印模3D打印与金属结构中束硬化伪影的减少-2022年

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Citation: Park, Y.; Yu, S.-M.
3D Printing of Tooth Impressions
Based on Multi-Detector Computed
Tomography Images Combined with
Beam Hardening Artifact Reduction
in Metal Structures. Appl. Sci. 2022,
12, 3339. https://doi.org/10.3390/
app12073339
Academic Editor: Claudio Belvedere
Received: 21 February 2022
Accepted: 24 March 2022
Published: 25 March 2022
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applied
sciences
Article
3D Printing of Tooth Impressions Based on Multi-Detector
Computed Tomography Images Combined with Beam
Hardening Artifact Reduction in Metal Structures
Yeon Park
1,2
and Seung-Man Yu
2,
*
1
Department of Radiology, Seoul National University Hospital, Seoul 03080, Korea; amadeus29@hanmail.net
2
Department of Radiologic Science, College of Medical Sciences, Jeonju University, Jeonju 55069, Korea
* Correspondence: ysm9993@jj.ac.kr; Tel.: +82-63-220-2382
Abstract:
We investigated the role of metal artifact reduction by taking 3D print impressions using
3D data of Computed Tomography (CT) images based on the algorithm applied. We manufactured a
phantom of a human mandible tooth made of gypsum and nickel alloy to measure the metal artifacts.
CT images were obtained by changing the phantom tube voltage and tube current. The signal intensity
of the image generated by the metal artifacts before and after the iterative metal artifact reduction
algorithm (iMAR) was measured. A 3D printing process was performed after converting the images,
before and after iMAR application, into STL files using InVesalius
version 3.1.1
by selecting the
conditions that minimized the effect of the artifact. Regarding metal artifacts, the Hounsfield unit
(HU) value showed low as the tube voltage increased. The iMAR-applied images acquired under the
same conditions showed a significantly lower HU. The artifacts, in the form of flashes, persisted in the
3D-printed product of the image not subjected to iMAR, but were largely removed in the 3D-printed
product following iMAR application. In this study, the application of iMAR and data acquired using
high tube voltage eliminated a significant portion of the metal artifacts, resulting in an impression
shape that was consistent with the human body.
Keywords: 3D printing; metal artifact reduction; radiography
1. Introduction
During periodontal diseases such as tooth decay, the shape of the tooth is acquired
using a dental impression. The treatment entails the insertion of a dental implant. An
irreversible hydrocolloid material, known as alginate, is used to obtain the dental impres-
sion conventionally [
1
,
2
]. However, in this conventional method, since the alginate must
be firmly maintained on the teeth, the patients may complain of discomfort during the
acquisition method. The peculiar smell of alginate is not only repulsive to the patient but
also affects the accuracy of the tooth shape during the patient’s movement whilst taking the
dental impression. In addition, areas in the tooth lacking firm bonding between alginate
and the tooth during the extraction process can lead to errors in the tooth shape. Therefore,
in order to overcome these limitations, and to alleviate patients’ discomfort, digital data
are being utilized to obtain impressions [3,4].
A 3D scanner does not generate the unique odor of alginate, and thus avoids patient
discomfort. The 3D scanner acquires the 3D surface data of the teeth and the model of the
tooth and, based on the 3D printout, generates an implant appropriate for the patient’s
periodontal disease [
5
,
6
]. The patient’s information is processed digitally, obviating the
need to store the patient’s dental plaster model. The storage and management of the
patient’s dental information is easy and the optimal treatment method can be established
via various simulations. The raw 3D data obtained with the scanner is converted into a
stereophotography CAD software file (STL) and output to a 3D printer [
7
,
8
]. However,
the accuracy of 3D scanners with digital advantages is limited in the oral cavity and by
Appl. Sci. 2022, 12, 3339. https://doi.org/10.3390/app12073339 https://www.mdpi.com/journal/applsci
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