Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Uncertainty in Measurement: Accuracy and Precision03:37

Uncertainty in Measurement: Accuracy and Precision

100.8K
Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. 
100.8K
Improving Translational Accuracy02:07

Improving Translational Accuracy

14.9K
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
14.9K
Introduction to Test of Independence01:21

Introduction to Test of Independence

3.0K
In statistics, the term independence means that one can directly obtain the probability of any event involving both variables by multiplying their individual probabilities. Tests of independence are chi-square tests involving the use of a contingency table of observed (data) values.
The test statistic for a test of independence is similar to that of a goodness-of-fit test:
3.0K
Hypothesis Test for Test of Independence01:16

Hypothesis Test for Test of Independence

8.1K
The test of independence is a chi-square-based test used to determine whether two variables or factors are independent or dependent. This hypothesis test is used to examine the independence of the variables. One can construct two qualitative survey questions or experiments based on the variables in a contingency table. The goal is to see if the two variables are unrelated (independent) or related (dependent). The null and alternative hypotheses for this test are:
H0: The two variables (factors)...
8.1K
lncRNA - Long Non-coding RNAs02:39

lncRNA - Long Non-coding RNAs

9.9K
In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA...
9.9K
Law of Independent Assortment02:03

Law of Independent Assortment

62.4K
While Mendel’s Law of Segregation states that the two alleles for one gene are separated into different gametes, a different question of how different genes are inherited remains. For example, is the gene for tall plants inherited with the gene for green peas? Mendel asked this question by experimenting with a dihybrid cross; a cross in which both parents are homozygous for two distinct traits resulting in an F1 generation that are heterozygous for both traits.
62.4K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Clinical implementation of an EU MDR-compliant point-of-care manufacturing framework for patient-specific 3D-printed PEEK implants in craniomaxillofacial reconstruction.

3D printing in medicine·2026
Same author

Surgical Performance of 3D-Printed Polyetheretherketone (PEEK) Patient-Specific Implants and Titanium Mesh in Clinically Matched Orbital Reconstruction: A Cadaveric Study.

Craniomaxillofacial trauma & reconstruction·2026
Same author

A Prospective, International, Multicentre Registry of Patients Undergoing Segmental Mandibular Defect Reconstruction After Mandibular Resection for Tumours and Drug-Induced Osteonecrosis: A Study Protocol.

Craniomaxillofacial trauma & reconstruction·2026
Same author

Comparison of the Ultrasonic Tip with Multidirectional Angular Cutting Geometry with the Straight Dentition Cutting in Bone Osteotomies with the Piezoelectric Technique.

Dentistry journal·2026
Same author

Consensus Report of Group 2 of the 1st Global Consensus for Clinical Guidelines for the Rehabilitation of the Edentulous Maxilla: Zygomatic, Standard-Length, and Short Implant-Supported Prostheses.

Clinical oral implants research·2026
Same author

A Clinical Decision-Making Algorithm for Botulinum Toxin Use in Temporomandibular Disorders and Bruxism.

Journal of clinical medicine·2026

Related Experiment Video

Updated: Jan 28, 2026

Mixed Reality Technology and Three-Dimensional Printing in Teaching: Heart Anatomy as an Example
06:18

Mixed Reality Technology and Three-Dimensional Printing in Teaching: Heart Anatomy as an Example

Published on: April 18, 2025

785

A Slicer-Independent Framework for Measuring G-Code Accuracy in Medical 3D Printing.

Michel Beyer1,2, Alexandru Burde3, Andreas E Roser1,2

  • 1Department of Oral and Cranio-Maxillofacial Surgery, University Hospital Basel, 4031 Basel, Switzerland.

Journal of Imaging
|January 27, 2026
PubMed
Summary
This summary is machine-generated.

Slicing software significantly impacts 3D printing accuracy. This study quantified deviations introduced by five slicers, finding errors below 0.1 mm, crucial for medical applications.

Keywords:
3D printingCAD/CAMG-codeimage processingvolume rendering

More Related Videos

3D Printing - Evaluating Particle Emissions of a 3D Printing Pen
06:44

3D Printing - Evaluating Particle Emissions of a 3D Printing Pen

Published on: October 9, 2020

9.1K
Rapid and Low-cost Prototyping of Medical Devices Using 3D Printed Molds for Liquid Injection Molding
10:43

Rapid and Low-cost Prototyping of Medical Devices Using 3D Printed Molds for Liquid Injection Molding

Published on: June 27, 2014

20.5K

Related Experiment Videos

Last Updated: Jan 28, 2026

Mixed Reality Technology and Three-Dimensional Printing in Teaching: Heart Anatomy as an Example
06:18

Mixed Reality Technology and Three-Dimensional Printing in Teaching: Heart Anatomy as an Example

Published on: April 18, 2025

785
3D Printing - Evaluating Particle Emissions of a 3D Printing Pen
06:44

3D Printing - Evaluating Particle Emissions of a 3D Printing Pen

Published on: October 9, 2020

9.1K
Rapid and Low-cost Prototyping of Medical Devices Using 3D Printed Molds for Liquid Injection Molding
10:43

Rapid and Low-cost Prototyping of Medical Devices Using 3D Printed Molds for Liquid Injection Molding

Published on: June 27, 2014

20.5K

Area of Science:

  • Biomedical Engineering
  • Additive Manufacturing
  • Computational Geometry

Background:

  • Accuracy in medical 3D printing is vital for patient-specific implants and anatomical models.
  • While printer performance is studied, the impact of slicing software on geometric fidelity remains less quantified.
  • The conversion of STL files to G-code by slicers can introduce deviations affecting final print accuracy.

Purpose of the Study:

  • To quantify slicer-induced G-code deviations by comparing G-code-derived geometries with their reference STL models.
  • To assess the influence of different slicing software on the geometric fidelity of 3D printed medical models.
  • To determine which slicing software introduces the least geometric error in the FDM workflow.

Main Methods:

  • Twenty mandibular models were processed using five slicers: PrusaSlicer, Cura, Simplify3D, Slic3r, and Fusion 360.
  • A custom Python workflow converted G-code to point clouds and reconstructed STL meshes with XY/Z corrections and surface extraction.
  • Accuracy was evaluated using Mean Surface Distance (MSD), Root Mean Square (RMS) deviation, and Volume Difference, with a calibration object for normalization.

Main Results:

  • Slicer-induced Mean Surface Distance (MSD) ranged from 0.071 to 0.095 mm, and Root Mean Square (RMS) deviation from 0.084 to 0.113 mm.
  • Volumetric differences were dependent on the slicing software used.
  • PrusaSlicer demonstrated the highest surface accuracy, while Simplify3D and Slic3r exhibited the best repeatability. Fusion 360 yielded the largest deviations.

Conclusions:

  • Slicing software introduces geometric deviations below 0.1 mm, representing a significant portion of the overall error in Fused Deposition Modeling (FDM) workflows.
  • The choice of slicing software critically influences the geometric accuracy of 3D printed medical models.
  • Understanding and mitigating slicer-induced errors are essential for advancing the reliability of medical 3D printing.