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Updated: Jun 24, 2025

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Mandibular bone segmentation from CT scans: Quantitative and qualitative comparison among software.

Talal Bin Irshad1, Giulia Pascoletti1, Francesco Bianconi1

  • 1Department of Engineering, University of Perugia, Perugia, Italy.

Dental Materials : Official Publication of the Academy of Dental Materials
|June 7, 2024
PubMed
Summary
This summary is machine-generated.

Choosing 3D reconstruction software for CT scans is complex. This study evaluated five software options using metrics like usability and accuracy, finding generally good mandible segmentation performance but significant differences in cost and time.

Keywords:
3D reconstructionCT scansDSCGeometric accuracyMandibleSegmentationUsability

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Area of Science:

  • Medical Imaging
  • Computer-Aided Surgery
  • Biomedical Engineering

Background:

  • A variety of software exists for 3D reconstruction from CT scans.
  • Software differs in cost, capabilities, and required a priori knowledge, making selection challenging.

Purpose of the Study:

  • To evaluate and compare the performance of different 3D reconstruction software.
  • To provide data to aid in selecting the most suitable software for specific applications.

Main Methods:

  • Established metrics including software usability, segmentation quality, geometric accuracy, mesh properties, and Dice Similarity Coefficient (DSC).
  • Evaluated five software packages: Mimics, D2P, Blue Sky Plan, Relu, and 3D Slicer.
  • Utilized four test cases, with the mandibular bone serving as the benchmark.

Main Results:

  • Relu software, leveraging AI, demonstrated excellent usability and ability to handle intricate geometries.
  • Segmentation time varied significantly, with Relu requiring substantially more time than Mimics.
  • Geometric distances were generally below 2.5 mm, with a maximum of 3.1 mm in critical areas.
  • Maximum Dice Similarity Coefficient (DSC) values reached 0.96 between specific software pairs (Mimics/Slicer, D2P/Mimics, D2P/Slicer).

Conclusions:

  • Mandible segmentation performance across the evaluated software was generally high.
  • Significant variations exist in geometric accuracy, usability, cost, and time requirements.
  • The provided information assists in making informed decisions when selecting 3D reconstruction software.