Overview - ISO/ASTM TR 52916:2022 (Additive manufacturing for medical - Data - Optimized medical image data)
ISO/ASTM TR 52916:2022 defines practices for creating optimized medical image data to support accurate medical additive manufacturing (MAM). It focuses on converting static imaging modalities (CT, MRI) and their DICOM outputs into high-fidelity 3D solid models suitable for 3D printing and other AM workflows. The report explains how imaging resolution, noise, tissue contrast and modality artefacts affect the accuracy of printed anatomical models and describes processing approaches to reduce those errors.
Key technical topics and requirements
- Medical image generation and error sources: Factors that introduce error during CT and MRI acquisition and reconstruction (slice thickness, noise, artefacts).
- Isotropic conversion and slice interval optimization: Reconfiguring slice spacing to improve volumetric accuracy from stacked 2D images.
- Image segmentation techniques: Thresholding, region growing, morphological methods, level-set and other segmentation approaches for defining regions of interest (ROI).
- Reconstruction and mesh processing: Steps from voxel/volume data to polygonal meshes; techniques such as marching cubes, mesh smoothing and mesh quality considerations.
- 3D visualization and rendering: Surface shaded rendering, volume rendering, ray casting and 3D texture mapping to inspect and validate models before fabrication.
- Image enhancement and preprocessing: Methods to reduce noise and improve contrast prior to segmentation.
- Minimizing software and equipment error: Verification approaches, tolerance considerations, and recommended evaluation models to assess computational and hardware-induced errors.
- Additional AM processing: Post-processing steps tailored for additive manufacturing, and guidance on medical CAD tolerances (informative annex).
Practical applications and who uses this standard
ISO/ASTM TR 52916 is intended for professionals and organizations involved in medical 3D printing and surgical planning, including:
- Medical AM system manufacturers and software developers
- Clinical teams using patient-specific anatomical models for pre-surgical planning and simulation
- Medical device and implant designers producing patient-specific implants, guides and prostheses
- Clinical educators and diagnostic model producers
- Quality assurance and regulatory personnel validating imaging-to-print workflows
Benefits include improved model accuracy, reproducible workflows from DICOM to printable geometry, and clearer guidance on reducing imaging- and software-related error.
Related standards
- ISO/ASTM 52900 - Additive manufacturing - General principles, fundamentals and vocabulary (referenced)
- Other referenced ISO standards for imaging terms and rendering (e.g., ISO 15708-1, ISO 14630, ISO 19262, ISO 18739, ISO 25178-2) as cited in the report.
Keywords: ISO/ASTM TR 52916:2022, additive manufacturing for medical, optimized medical image data, medical AM, CT, MRI, DICOM, segmentation, mesh smoothing, isotropic conversion, 3D printing medical models.