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Orbital Volume Analysis of Midfacial Fractures Using Additive Manufacturing Technologies

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International Conference on Emerging Trends in Engineering (ICETE)

Part of the book series: Learning and Analytics in Intelligent Systems ((LAIS,volume 2))

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Abstract

Midfacial fractures occur in a variety of patterns. For doctors to understand the severity of these fractures, it is important for them to identify the types of fracture and its clinical relevance. This complexity can be solved by having a three-dimensional physical model using Additive Manufacturing (AM) Technology. The aim of this paper is to do Orbital volume analysis of Midfacial fractures by 3D Printing medical models of the skull using Fused Deposition Modelling (FDM) process. The methodology involves collection of Pre-Operative and Post-Operative CT scan images of the patient in DICOM format and converting it to 3D CAD model using InVesalius medical imaging software. The generated 3D CAD model is saved in .STL format and is then transferred to Flashforge FDM machine for printing Pre-Operative and Post-Operative 3D medical models. Measurements are taken on both Pre-Operative and Post-Operative 3D printed medical models at fixed landmarks to calculate the Orbital volume. These values are compared with Unfractured orbit of skull to find out the percentage of restoration.

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Acknowledgement

The Authors would like to thank UGC, South Eastern Regional Office, Hyderabad, as this research is carried out as a part of UGC Minor Research Project titled “Assessment of Dimensional Accuracy of Facial (Zygomatic) bone fractures reduction using Additive Manufacturing: a Randomized Control Study” Proposal No. 1204, Letter No. F. No: 4-4/2015-16/MRP/UGC-SERO, Dt. Oct 2016 sanctioned to Dr. L. Siva Rama Krishna.

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Correspondence to Shiva Dharshan Vanapalli .

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Siva Rama Krishna, L., Vanapalli, S.D., Venkatesh, S., Potturi, A. (2020). Orbital Volume Analysis of Midfacial Fractures Using Additive Manufacturing Technologies. In: Satapathy, S., Raju, K., Molugaram, K., Krishnaiah, A., Tsihrintzis, G. (eds) International Conference on Emerging Trends in Engineering (ICETE). Learning and Analytics in Intelligent Systems, vol 2. Springer, Cham. https://doi.org/10.1007/978-3-030-24314-2_67

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  • DOI: https://doi.org/10.1007/978-3-030-24314-2_67

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-24313-5

  • Online ISBN: 978-3-030-24314-2

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