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

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XV Mediterranean Conference on Medical and Biological Engineering and Computing – MEDICON 2019 (MEDICON 2019)

Part of the book series: IFMBE Proceedings ((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.

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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.

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Authors and Affiliations

  1. Institute of Biostructures and Bioimaging, Italian National Research Council, Naples, Italy

    Maria Agnese Pirozzi, Mario Magliulo & Bruno Alfano

  2. Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Naples, Italy

    Maria Agnese Pirozzi, Emilio Andreozzi & Mario Cesarelli

  3. Istituti Clinici Scientifici Maugeri S.p.A. – Società Benefit, Pavia, Italy

    Emilio Andreozzi & Mario Cesarelli

  4. Institute for Biomedical and Neural Engineering, Reykjavík University, Reykjavík, Iceland

    Paolo Gargiulo

  5. Department of Science, Landspítali University Hospital, Reykjavík, Iceland

    Paolo Gargiulo

Authors
  1. Maria Agnese Pirozzi
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  2. Emilio Andreozzi
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  3. Mario Magliulo
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  4. Paolo Gargiulo
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  5. Mario Cesarelli
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  6. Bruno Alfano
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Corresponding author

Correspondence to Maria Agnese Pirozzi .

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Editors and Affiliations

  1. University of Coimbra, Coimbra, Portugal

    Jorge Henriques

  2. Universidade do Minho, Braga, Portugal

    Nuno Neves

  3. University of Coimbra, Coimbra, Portugal

    Paulo de Carvalho

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Pirozzi, M.A., Andreozzi, E., Magliulo, M., Gargiulo, P., Cesarelli, M., Alfano, B. (2020). Automated Design of Efficient Supports in FDM 3D Printing of Anatomical Phantoms. In: Henriques, J., Neves, N., de Carvalho, P. (eds) XV Mediterranean Conference on Medical and Biological Engineering and Computing – MEDICON 2019. MEDICON 2019. IFMBE Proceedings, vol 76. Springer, Cham. https://doi.org/10.1007/978-3-030-31635-8_35

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  • DOI: https://doi.org/10.1007/978-3-030-31635-8_35

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-31634-1

  • Online ISBN: 978-3-030-31635-8

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