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Automated Design of Efficient Supports in FDM 3D Printing of Anatomical Phantoms

  • Maria Agnese PirozziEmail author
  • Emilio Andreozzi
  • Mario Magliulo
  • Paolo Gargiulo
  • Mario Cesarelli
  • Bruno Alfano
Conference paper
Part of the IFMBE Proceedings book series (IFMBE, volume 76)

Abstract

Recent improvements in image segmentation techniques enabled the (semi)automatic extraction of biostructures surfaces from 3D medical imaging data. The diffusion of 3D printing technologies promoted their introduction in the medical field, giving rise to several applications, such as the development of 3D-printed anatomical imaging phantoms. These devices provide controlled experimental environments for the improvement of medical imaging techniques, as they mimic the morphological and physiological features of different body parts. However, to obtain a 3D printable model from medical imaging data, different post-processing steps are needed, which require a considerable effort. Supports generation is often a critical task, as it requires to find the minimum amount of support structures necessary to hold a part in place during the printing process. This is particularly difficult for complex anthropomorphic models, for which a high printing level of detail, along with a reasonable number of internal supports, is usually needed. In this paper, an automatic method for the design of efficient support structures is proposed, which is suitable for 3D printing of complex anatomical phantoms, even with non-professional FDM 3D printers. A custom design software was developed, which places paraboloid-shaped shells to support all and only the critical points of the 3D model. This provided different advantages over support generation by means of common slicing software, allowing a reduction of material waste and printing times, along with an easier and faster dissolution of soluble supports for the clean-up of phantoms empty volumes.

Keywords

3D printing FDM Supports design Anatomical phantoms Medical imaging 

Notes

Acknowledgment

Funding by the CNR Strategic Project “The Aging: Technological and Molecular Innovations Aiming to Improve the Health of Older Citizens” (http://www.progettoinvecchiamento.it) and by the Italian Ministry for Education, University and Research (Project MOLIM ONCOBRAIN LAB) is gratefully acknowledged.

Conflict of Interest

The authors declare that they have no conflict of interest.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Institute of Biostructures and BioimagingItalian National Research CouncilNaplesItaly
  2. 2.Department of Electrical Engineering and Information TechnologiesUniversity of Naples Federico IINaplesItaly
  3. 3.Istituti Clinici Scientifici Maugeri S.p.A. – Società BenefitPaviaItaly
  4. 4.Institute for Biomedical and Neural EngineeringReykjavík UniversityReykjavíkIceland
  5. 5.Department of ScienceLandspítali University HospitalReykjavíkIceland

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