Page 307 - IJB-9-1

International Journal of Bioprinting

RESEARCH ARTICLE
Error assessment and correction for

extrusion-based bioprinting using computer
vision method

Changxi Liu , Chengliang Yang , Jia Liu *, Yujin Tang *, Zhengjie Lin ,
2,3
1,2
2,3
4
2,3
Long Li , Hai Liang , Weijie Lu , Liqiang Wang *
5
5
1,2
1,2
1 State Key Laboratory of Metal Matrix Composites, School of Material Science and Engineering,
Shanghai Jiao Tong University, Shanghai, 200240, China
2 National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai 200240,
China
3
Department of Orthopaedics, Affiliated Hospital of Youjiang Medical University for Nationalities,
Guangxi Key Laboratory of Basic and Translational Research of Bone and Joint Degenerative
Diseases, Baise, 533000, Guangxi, China
4 3D Printing Clinical Translational and Regenerative Medicine Center, Shenzhen Shekou People’s
Hospital, Shenzhen, 518060, China
5
Department of Stomatology, Shenzhen Shekou People’s Hospital, Shenzhen, 518060, China
(This article belongs to the Special Issue: Related to 3D printing technology and materials)
Abstract
Bioprinting offers a new approach to addressing the organ shortage crisis. Despite
recent technological advances, insufficient printing resolution continues to be one
of the reasons that impede the development of bioprinting. Normally, machine axes
*Corresponding authors:
Jia Liu (liujia@ymcn.edu.cn) movement cannot be reliably used to predict material placement, and the printing
Yujin Tang (tangyujin@ymcn.edu.cn) path tends to deviate from the predetermined designed reference trajectory in vary-
Liqiang Wang ing degrees. Therefore, a computer vision-based method was proposed in this study
(wang_liqiang@sjtu.edu.cn)
to correct trajectory deviation and improve printing accuracy. The image algorithm
Citation: Liu C, Yang C, Liu J, et calculated the deviation between the printed trajectory and the reference trajectory
al., 2023, Error assessment and
correction for extrusion-based to generate an error vector. Furthermore, the axes trajectory was modified according
bioprinting using computer vision to the normal vector approach in the second printing to compensate for the devia-
method. Int J Bioprint, 9(1): 644. tion error. The highest correction efficiency that could be achieved was 91%. More
https://doi.org/10.18063/ijb.v9i1.644
significantly, we discovered that the correction results, for the first time, were in a
Received: July 14, 2022 normal distribution instead of a random distribution.
Accepted: August 30, 2022
Published Online: November 16,
2022
Keywords: Bioprinting; Computer vision; Error detection; Sobel operator
Copyright: © 2022 Author(s).
This is an Open Access article
distributed under the terms of the
Creative Commons Attribution
License, permitting distribution 1. Introduction
and reproduction in any medium,
provided the original work is Organ shortage is a serious social health crisis. A report from the University of Minnesota
properly cited. states that approximately 90,000 people require kidney transplant, but only 1,500 people
[1]
Publisher’s Note: Whioce have undergone kidney transplants in 2018 . The shortage of fitting and propitious
Publishing remains neutral with organs for transplantation has always been a medical concern [2-4] . Building organs from
regard to jurisdictional claims in
published maps and institutional scratch to explore entirely new cell configurations is the main feature of bioprinting,
affiliations. which is an emerging scientific field that has potential to solve this organ shortage crisis [5,6] .

Volume 9 Issue 1 (2023) 299 https://doi.org/10.18063/ijb.v9i1.644