| Abstract Scope |
Traditional approaches to 3D printing anatomical models rely on mesh-based segmentation, forcing complex volumetric medical imagery into surface-only representations compatible with standard slicers. This simplification results in models that primarily capture external shape, significantly limiting their utility in real-world medical applications. In contrast, inkjet-based 3D printing enables fully volumetric fabrication, combining transparency with subtle gradations in color and material to create tactile, functional models made from hard, soft, and liquid materials. In this talk, we introduce a new medical imaging workflow integrated into OpenVCAD, an existing platform for functionally graded design. This extension processes raw medical images directly, bypassing traditional segmentation, and maps radiodensity into material distributions. We demonstrate how this workflow generates patient-specific, 3D-printed models that preserve both visual and mechanical fidelity. Such models enhance internal anatomy visualization and can provide realistic simulation of soft tissue behavior, making them well-suited not only for preoperative planning but also hands-on training. |