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

You might also read

Related Articles

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

Sort by
Same author

One-year follow-up after fractionated ultra-high-dose-rate FLASH radiotherapy in patient with extramammary Paget disease of the scrotum.

Precision radiation oncology·2026
Same author

Pilot longitudinal integrated transcriptomic-metabolomic study reveals immune and metabolic signatures in non-hospitalized healthcare workers with long COVID.

Frontiers in cellular and infection microbiology·2026
Same author

Inheritance patterns of mitochondrial DNA in multi-generational maternal pedigrees: Insights from mitochondrial whole-genome sequencing.

Forensic science international. Genetics·2026
Same author

A nomogram for predicting free flap necrosis in soft tissue reconstruction of lower limbs: a retrospective cohort study.

Frontiers in medicine·2026
Same author

Urinary volatile organic compound metabolites and premature menopause: Population-based, network toxicology, and experimental evidence with a focus on HEMA.

Ecotoxicology and environmental safety·2026
Same author

A novel HN-AD strain Paenibacillus glycanilyticus DQ-1 with high-efficiency nitrogen removal capacity: genomic insights into its nitrogen metabolic mechanism.

BMC microbiology·2026
Same journal

Advancing Modular Microfluidics: Stereolithographic 3D Printing of Reconfigurable Connectors for Bioanalytical Applications.

International journal of bioprinting·2026
Same journal

Exploring the mechanical strength, antimicrobial performance, and bioactivity of 3D-printed silicon nitride-PEEK composites in cervical spinal cages.

International journal of bioprinting·2025
Same journal

Toward robust and reproducible pluripotent stem cell expansion in bioprinted GelMA constructs.

International journal of bioprinting·2025
Same journal

3D bioartificial stretchable scaffolds mimicking the mechanical hallmarks of human cardiac fibrotic tissue.

International journal of bioprinting·2024
Same journal

3D-printed hydrogels dressings with bioactive borate glass for continuous hydration and treatment of second-degree burns.

International journal of bioprinting·2024
Same journal

Enhanced osteogenesis and bactericidal performance with additively manufactured MgO and Cu-added CpTi for load-bearing implants.

International journal of bioprinting·2023
See all related articles

Related Experiment Video

Updated: Aug 8, 2025

Design and Validation of a Volumetric-extrusion Bioprinter for Bioprinting of Soluble Basement Membrane Extract for Translational Research
08:27

Design and Validation of a Volumetric-extrusion Bioprinter for Bioprinting of Soluble Basement Membrane Extract for Translational Research

Published on: March 28, 2025

303

Error assessment and correction for extrusion-based bioprinting using computer vision method.

Changxi Liu1,2, Chengliang Yang2,3, Jia Liu2,3

  • 1State Key Laboratory of Metal Matrix Composites, School of Material Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.

International Journal of Bioprinting
|February 27, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a computer vision method to enhance bioprinting accuracy by correcting trajectory deviations. This novel approach significantly improves printing resolution and ensures more predictable material placement for organ bioprinting.

Keywords:
BioprintingComputer visionError detectionSobel operator

More Related Videos

Automated Robotic Dispensing Technique for Surface Guidance and Bioprinting of Cells
10:14

Automated Robotic Dispensing Technique for Surface Guidance and Bioprinting of Cells

Published on: November 18, 2016

7.3K
Viability of Bioprinted Cellular Constructs Using a Three Dispenser Cartesian Printer
07:05

Viability of Bioprinted Cellular Constructs Using a Three Dispenser Cartesian Printer

Published on: September 22, 2015

10.1K

Related Experiment Videos

Last Updated: Aug 8, 2025

Design and Validation of a Volumetric-extrusion Bioprinter for Bioprinting of Soluble Basement Membrane Extract for Translational Research
08:27

Design and Validation of a Volumetric-extrusion Bioprinter for Bioprinting of Soluble Basement Membrane Extract for Translational Research

Published on: March 28, 2025

303
Automated Robotic Dispensing Technique for Surface Guidance and Bioprinting of Cells
10:14

Automated Robotic Dispensing Technique for Surface Guidance and Bioprinting of Cells

Published on: November 18, 2016

7.3K
Viability of Bioprinted Cellular Constructs Using a Three Dispenser Cartesian Printer
07:05

Viability of Bioprinted Cellular Constructs Using a Three Dispenser Cartesian Printer

Published on: September 22, 2015

10.1K

Area of Science:

  • Bioprinting
  • Regenerative Medicine
  • Computer Vision

Background:

  • Bioprinting is a promising solution for the organ shortage crisis.
  • Current bioprinting technology faces limitations in printing resolution and trajectory accuracy.
  • Machine axis movements do not reliably predict material placement, leading to deviations from the intended path.

Purpose of the Study:

  • To develop a computer vision-based method for correcting trajectory deviations in bioprinting.
  • To improve the accuracy and resolution of the bioprinting process.
  • To address the limitations hindering the advancement of bioprinting technology.

Main Methods:

  • A computer vision algorithm was employed to detect and quantify trajectory deviations.
  • An error vector was generated by comparing the printed path to the reference trajectory.
  • The printing axes trajectory was modified using a normal vector approach in a second printing pass to compensate for errors.

Main Results:

  • The proposed method achieved a highest correction efficiency of 91%.
  • For the first time, correction results exhibited a normal distribution, moving away from random distributions.
  • This demonstrates a significant improvement in the predictability and accuracy of the bioprinting process.

Conclusions:

  • Computer vision-based trajectory correction is effective in enhancing bioprinting accuracy.
  • The method offers a viable solution to overcome resolution limitations in bioprinting.
  • This advancement contributes to the potential of bioprinting for addressing organ shortages.