Advanced Image Segmentation and Modeling – A Review of the 2021–2022 Thematic Series

Abstract

Medical 3D printing is a form of manufacturing that benefits patient care, particularly when the 3D printed part is patient-specific and either enables or facilitates an intervention for a specific condition. Most of the patient-specific medical 3D printing begins with volume based medical images of the patient. Several digital manipulations are typically performed to prescribe a final anatomic representation that is then 3D printed. Among these are image segmentation where a volume of interest such as an organ or a set of tissues is digitally extracted from the volumetric imaging data. Image segmentation requires medical expertise, training, software, and effort. The theme of image segmentation has a broad intersection with medical 3D printing. The purpose of this editorial is to highlight different points of that intersection in a recent thematic series within 3D Printing in Medicine.

Embedded 3D Printing of Thermally‐Cured Thermoset Elastomers and the Interdependence of Rheology and Machine Pathing

“…[ 22 ] To date, most extrusion‐based 3D printing, including FRE, has used established FDM slicing software, which assumes that 1) filaments are flattened onto the print platform during extrusion, with a thin and wide elliptical cross‐section, and 2) filaments do not deform after extrusion ( Figure A,B). [ 24–26 ] This expectation holds for FDM because the thermoplastic filament is melted, extruded, and flattened against the layer below it, where it subsequently rapidly cools and solidifies. In FRE, the thermally‐cured ink is slow to cure and extruded within a yield‐stress support bath instead of onto a build platform.…”