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International Journal of Bioprinting In situ defect detection and feedback control with P-OCT

A

B

Figure 1. The closed-loop feedback control loop (A) and the algorithm flow (B) for in situ defect detection and feedback control with 3D P-OCT. 3D
P-OCT: Three-dimensional extrusion-based bioprinter-associated optical coherence tomography.

A B pressure and velocity, and reducing FL and LT errors are
the premise of high-fidelity 3D bioprinting. Therefore, new
quantification methods for FL and LT were first determined,
and then, the corresponding feedback mechanisms were
pre-built for different defects during 3D bioprinting. By
combining 3D P-OCT data and the design model, the layer
fidelity and overall fidelity could be further assessed for the
C D construct.

2.3.1. FS
In the previous work, the projection view in depth (z)
of the 3D P-OCT data was used for the FS analysis.
To avoid possible errors due to projection, 3D P-OCT
data were used for more accurate FS quantification, as
Figure 2. Layer thickness (LT) quantification based on the design model shown in Figure 2. The material of hydroxyapatite (Hap)
and three-dimensional extrusion-based bioprinter-associated optical was selected in this study, which was purchased from
coherence tomography (3D P-OCT) data. (A) GCode nodes before Shanghai Macklin Biochemical Co., Ltd. (China). The
interpolation corresponding to the filament in Figure 3A. (B) GCode Hap paste was prepared by mixing 1.8 mL glycerin, 0.2 g
nodes after interpolation. (C) The registration results of the design model
based on GCode nodes and 3D P-OCT data. (D) The spatial distribution of ammonium polyacrylate, 0.24 g polymethyl cellulose,
of LT. and 7 g Hap in 4.5 mL deionized water. After stirring for

Volume 9 Issue 1 (2023) 50 https://doi.org/10.18063/ijb.v9i1.624