PorMe: A validated open-source image-based pore size and porosity measurement tool for 3D-printed structures

PorMe:一款经过验证的开源图像式3D打印结构孔径和孔隙率测量工具。

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Abstract

The paper presents a non-destructive image analysis tool for characterizing in situ the inner micro-architectural features of 3D-printed scaffolds for tissue engineering applications. The study aims to provide a high throughput method for assessing geometrical porous and fiber-based properties such as fiber diameter, orientation, pore size, and porosity. Through this study, an open-source image-based software has been created that uses images acquired in each vertical plane during the printing process. The images are automatically added one above the other and thus a series of three-dimensional geometric properties of the printed structures are analyzed. The method was validated by using 3D-cilindrical scaffolds of 10 mm diameter and 17 mm height, with pore size around 400 µm and porosity range of 40-60 %. It was demonstrated a high porosity prediction and homogeneous inner architecture between our current method, Archimedes-derived porosity, and a high standard microCT-based 3D analysis. This work also details the steps of the porosity measurement (PorMe) algorithm, which involves image acquisition, segmentation, invalid pore determination, pore size calculation, and porosity determination in a high-throughput and non-destructive manner. In situ, non-destructive image analysis tool to assess scaffold geometrical properties Layer-wise assessment of pore size, fiber diameter and orientation as opposed to just outer (top and bottom) layers Open-source tools used to develop the image analysis tool, to be made available for the research community.

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