scholarly journals Dimensional Accuracy Comparison of Physical Models Generated by Digital Impression/3D-Printing or Analog Impression/Plaster Methods

2021 ◽  
Vol 15 (3) ◽  
pp. 562-568
Author(s):  
Luciana Paula Benicio Arcas ◽  
João Paulo Mendes Tribst ◽  
Kusai Baroudi ◽  
Marina Amaral ◽  
Lais Regiane da Silva-Concílio ◽  
...  
Keyword(s):  
3D Printing ◽  
Dimensional Accuracy ◽  
Physical Models ◽  
Digital Impression ◽  
Accuracy Comparison

Results of studying the dimensional accuracy of the bases of complete removable prostheses made using 3D printing and traditional technologies

2020 ◽  
pp. 34-39
Author(s):  
Vokulova Yu.A. Vokulova ◽  
E.N. Zhulev
Keyword(s):  
3D Printing ◽  
Traditional Method ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Digital Technologies ◽  
Dimensional Accuracy ◽  
3D Printer ◽  
Significance Level ◽  
Average Value ◽  
The Difference

This article presents the results of studying the dimensional accuracy of the bases of complete removable prostheses made using a 3D printer and the traditional method. Bases of complete removable prostheses were made using an intraoral laser scanner iTero Cadent (USA) and a 3D printer Asiga Max UV (Australia). To study the dimensional accuracy of the bases of complete removable prostheses, we used the DentalCAD 2.2 Valletta software. The Nonparametric Wilcoxon W-test was used for statistical analysis of the obtained data. We found that the average value of the difference with the standard for bases made using digital technologies is 0.08744±0.0484 mm. The average value of the difference with the standard for bases made by the traditional method is 0.5654±0.1611 mm. Based on these data, we concluded that the bases of complete removable prostheses made using modern digital technologies (intraoral laser scanning and 3D printer) have a higher dimensional accuracy compared to the bases of complete removable prostheses made using the traditional method with a significance level of p<0.05 (Wilcoxon's W-test=0, p=0.031). Keywords: digital technologies in dentistry, digital impressions, intraoral scanner, 3D printing, ExoCAD, complete removable dentures.

Comparison of Direct and Indirect Scanners in Digital Impression Systems: A Narrative Review

2021 ◽  
Author(s):  
Mahsa Abbasi ◽  
Behnaz Ebadian ◽  
Negin Aminianpour
Keyword(s):  
Clinical Studies ◽  
Dimensional Accuracy ◽  
Clinical Results ◽  
Digital Impression ◽  
Lower Amount ◽  
Intraoral Scanner ◽  
Marginal Gap ◽  
Accuracy Rate ◽  
Impression Materials ◽  
Internal Gap

Introduction: Digital impression tools are an alternative to old impression materials and have developed significantly in recent years. These systems generally include two types of scanners: direct and indirect scanners. This article aimed to review and compare these two types of scanners. Description: Data were collected by reviewing a total of forty articles on dimensional accuracy, a combination of scans, and internal and marginal gaps for comparison of direct and indirect scanners. These articles were retrieved from PubMed and Scopus and published between 2010 and 2020 using the following keywords: intraoral scanner, lab scanner, marginal gap, internal gap, and accuracy rate. Results: Direct scanners had a lower amount of marginal and internal gaps, while indirect scanners had a lower deviation in more prepared teeth in the half and full arch due to the ability of stitching scans. Regarding the dimensional accuracy, the results of studies were inconsistent, but clinical studies pointed to the superiority of indirect scanners. The type of scanner suggested being selected depending on conditions such as the size of area, time, convenience of procedure, etc. The clinical results of both types of scanners were clinically acceptable.

scholarly journals 3D Printed Model of Airway for Clinical Simulation

2020 ◽  
Vol 8 (2) ◽  
pp. 50-56
Author(s):  
Maheswaran Viyannan ◽  
Pananghat A. Kumar ◽  
Sreedharkumar Eswarswamy ◽  
Gunaseelan Murugesan ◽  
Karthikeyan Ramaraju
Keyword(s):  
3D Printing ◽  
Medical Curriculum ◽  
Functional Model ◽  
Tracheobronchial Tree ◽  
Training System ◽  
Physical Models ◽  
Printing Technology ◽  
Clinical Simulation ◽  
3D Printing Technology ◽  
Axial Ct

Background: The present medical curriculum aims at training the students to be proficient in performing techniques required for clinical practice. This is best achieved through clinical simulation, which has emerged as a successful method for clinical learning. Residents in respiratory medicine need to be trained in the procedure of bronchoscopy for which a functional model of the airway is required. Airway mannequins for this purpose can be produced using 3D printing technology, which involves the usage of sophisticated software. Subjects and Methods: Serial axial CT images of the chest, revealing details of the respiratory tract were selected as the base resource to recreate the bronchial tree by 3D printing. This DICOM (Digital Imaging and Communications in Medicine) images after conversion into STL (Stero lithography) format were transferred into a 3D printer and physical models were made from these data, using Vero clear and rubber. This model which had a life-like form and consistency required for practicing the skill was connected to an airway mannequin using an adaptor to practice the skill. Conclusions: Axial CT scan images provide the base data for reconstructing the airway of a patient, using 3D printing technology and appropriate software. Such reconstructions can be used to produce a functional model of the airway, which can be used for training in bronchoscopy. The training system could be connected to a monitor thereby facilitating tracking of the probe of the bronchoscope. Repeated trials make the trainees perfect their technique. Our attempt to replicating the tracheobronchial tree for such training has been a success.

3D Printing of Medical Models: A Literature Review

2017 ◽  
Author(s):  
Xingjian Wei ◽  
Li Zeng ◽  
Zhijian Pei
Keyword(s):  
3D Printing ◽  
Literature Review ◽  
Medical Curriculum ◽  
Industrial Applications ◽  
Physical Models ◽  
Research Directions ◽  
Anatomical Structures ◽  
Medical Models ◽  
3D Printed ◽  
Anatomy Teaching

Medical models are physical models of human or animal anatomical structures such as skull and heart. Such models are used in simulation and planning of complex surgeries. They can also be utilized for anatomy teaching in medical curriculum. Traditionally, medical models are fabricated by paraffin wax or silicone casting. However, this method is time-consuming, of low quality, and not suitable for personalization. Recently, 3D printing technologies are used to fabricate medical models. Various applications of 3D printed medical models in surgeries and anatomy teaching have been reported, and their advantages over traditional medical models have been well-documented. However, 3D printing of medical models bears some special challenges compared to industrial applications of 3D printing. This paper reviews more than 50 publications on 3D printing of medical models between 2006 and 2016, and discusses knowledge gaps and potential research directions in this field.

Transiting between Representation Technologies and Teaching/Learning Descriptive Geometry

2016 ◽  
pp. 250-273 ◽  
Author(s):  
Janice de Freitas Pires ◽  
Luisa Dalla Vecchia ◽  
Adriane Almeida da Silva Borda
Keyword(s):  
Virtual Reality ◽  
Augmented Reality ◽  
3D Printing ◽  
Laser Cutting ◽  
Digital Fabrication ◽  
Physical Models ◽  
Descriptive Geometry ◽  
Parametric Modelling ◽  
Digital Representation ◽  
Teaching Learning

Teaching descriptive geometry, in the context of this study, is characterized by the continuous investment in recognizing digital representation technologies which can enhance the didactic activities in architectural training. This study describes this trajectory which includes the use of virtual reality, augmented reality and parametric modelling, as well as freehand drawing and the production of physical models both by automating the unfolding process and by digital fabrication processes of 3D printing and laser cutting. In addition to questioning the relevance and sustainability of the infrastructure needed to ensure the continuation of this trajectory, the potentialities identified in each of the learning activities that have been structure, are shown. Although these potentialities are specific to this context, it is considered that this type of record contributes to understand the issues being faced in teaching practices.

scholarly journals Surface Roughness Investigation of Poly-Jet 3D Printing

Mathematics ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1758
Author(s):  
Nectarios Vidakis ◽  
Markos Petousis ◽  
Nikolaos Vaxevanidis ◽  
John Kechagias
Keyword(s):  
Surface Roughness ◽  
3D Printing ◽  
Surface Quality ◽  
Back Propagation ◽  
Physical Models ◽  
Layer By Layer ◽  
Linear Regression Models ◽  
Feed Forward Back Propagation ◽  
The Impact

An experimental investigation of the surface quality of the Poly-Jet 3D printing (PJ-3DP) process is presented. PJ-3DP is an additive manufacturing process, which uses jetted photopolymer droplets, which are immediately cured with ultraviolet lamps, to build physical models, layer-by-layer. This method is fast and accurate due to the mechanism it uses for the deposition of layers as well as the 16 microns of layer thickness used. Τo characterize the surface quality of PJ-3DP printed parts, an experiment was designed and the results were analyzed to identify the impact of the deposition angle and blade mechanism motion onto the surface roughness. First, linear regression models were extracted for the prediction of surface quality parameters, such as the average surface roughness (Ra) and the total height of the profile (Rt) in the X and Y directions. Then, a Feed Forward Back Propagation Neural Network (FFBP-NN) was proposed for increasing the prediction performance of the surface roughness parameters Ra and Rt. These two models were compared with the reported ones in the literature; it was revealed that both performed better, leading to more accurate surface roughness predictions, whilst the NN model resulted in the best predictions, in particular for the Ra parameter.

scholarly journals One Step before 3D Printing—Evaluation of Imaging Software Accuracy for 3-Dimensional Analysis of the Mandible: A Comparative Study Using a Surface-to-Surface Matching Technique

Materials ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 2798 ◽  
Author(s):  
Antonino Lo Giudice ◽  
Vincenzo Ronsivalle ◽  
Cristina Grippaudo ◽  
Alessandra Lucchese ◽  
Simone Muraglie ◽  
...  
Keyword(s):  
Computed Tomography ◽  
3D Printing ◽  
Cone Beam Computed Tomography ◽  
High Reliability ◽  
Automatic Segmentation ◽  
Physical Models ◽  
Cone Beam ◽  
Manual Segmentation ◽  
Semiautomatic Segmentation ◽  
Deviation Analysis

The accuracy of 3D reconstructions of the craniomaxillofacial region using cone beam computed tomography (CBCT) is important for the morphological evaluation of specific anatomical structures. Moreover, an accurate segmentation process is fundamental for the physical reconstruction of the anatomy (3D printing) when a preliminary simulation of the therapy is required. In this regard, the objective of this study is to evaluate the accuracy of four different types of software for the semiautomatic segmentation of the mandibular jaw compared to manual segmentation, used as a gold standard. Twenty cone beam computed tomography (CBCT) with a manual approach (Mimics) and a semi-automatic approach (Invesalius, ITK-Snap, Dolphin 3D, Slicer 3D) were selected for the segmentation of the mandible in the present study. The accuracy of semi-automatic segmentation was evaluated: (1) by comparing the mandibular volumes obtained with semi-automatic 3D rendering and manual segmentation and (2) by deviation analysis between the two mandibular models. An analysis of variance (ANOVA) was used to evaluate differences in mandibular volumetric recordings and for a deviation analysis among the different software types used. Linear regression was also performed between manual and semi-automatic methods. No significant differences were found in the total volumes among the obtained 3D mandibular models (Mimics = 40.85 cm3, ITK-Snap = 40.81 cm3, Invesalius = 40.04 cm3, Dolphin 3D = 42.03 cm3, Slicer 3D = 40.58 cm3). High correlations were found between the semi-automatic segmentation and manual segmentation approach, with R coefficients ranging from 0,960 to 0,992. According to the deviation analysis, the mandibular models obtained with ITK-Snap showed the highest matching percentage (Tolerance A = 88.44%, Tolerance B = 97.30%), while those obtained with Dolphin 3D showed the lowest matching percentage (Tolerance A = 60.01%, Tolerance B = 87.76%) (p < 0.05). Colour-coded maps showed that the area of greatest mismatch between semi-automatic and manual segmentation was the condylar region and the region proximate to the dental roots. Despite the fact that the semi-automatic segmentation of the mandible showed, in general, high reliability and high correlation with the manual segmentation, caution should be taken when evaluating the morphological and dimensional characteristics of the condyles either on CBCT-derived digital models or physical models (3D printing).

scholarly journals 855 Patient Specific Digital Modelling And 3D Printing of Abdominal Anatomy- The Next Frontier in Surgical Simulation?

2021 ◽  
Vol 108 (Supplement_2) ◽  
Author(s):  
J Fletcher ◽  
C Myles ◽  
D Miskovic ◽  
J Jones ◽  
R Cahill
Keyword(s):  
3D Printing ◽  
Injection Moulding ◽  
Surgical Simulation ◽  
Low Cost ◽  
Physical Models ◽  
Patient Specific ◽  
Phase Imaging ◽  
Imaging Data ◽  
Digital Models ◽  
Operative Planning

Abstract Introduction Innovations in digital technologies afford new opportunities in surgical education. We describe a novel method of combining medical imaging data with virtual 3D modelling and printing techniques that could facilitate patient specific pre-operative planning and rehearsal. Method A series of silicone castings was produced to simulate upper abdominal viscera using a novel polyvinyl alcohol (PVA) injection moulding method. Digital models were generated by segmenting CT dual phase imaging in ITK-SNAP. A 3D polygon mesh was exported and optimised in the computer graphics software: Blender. Two 3D printers were used to manufacture a dissolvable mould of the digital models. Moulds were injected with coloured silicones and dissolved in water to reveal the multicolour/multi-material models. Results The silicone models retained the anatomical detail of the digitally segmented CT data sets. The multi-colour models were achieved with a single print and at very low cost (approx. £248/ model) and possessed varying shore hardness between viscera recreating lifelike fidelity. Conclusions The hybrid 3D printing/injection moulding method offers an avenue to realistic surgical and anatomical simulation. A combination of both virtual models and 3D physical models may provide an enhanced surgical experience for preoperative and intraoperative planning allowing patient specific rehearsal.

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