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This study aims to demonstrate the implementation of a region growing algorithm as a segmentation method in microcomputed tomography (micro–CT) studies in endodontics. Twelve one-rooted teeth were scanned in the four primary stages of the endodontic procedure—before treatment and after shaping, filling and retreatment. Forty-eight models were accomplished, images were analyzed, and the region growing algorithm was seeded to achieve fast and precise segmentation of the canal space. The segmentation was successful in all specimens.

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The Application of Region Growing as a Segmentation Method in Micro–CT Studies in Endodontics

  • 会议论文

  • 发表日期：

    2025年

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  • Miryana Raykovska,
  • Evgeni Koytchev,
  • Ivan Georgiev,
  • Maria Datcheva

摘要

This study aims to demonstrate the implementation of a region growing algorithm as a segmentation method in microcomputed tomography (micro–CT) studies in endodontics. Twelve one-rooted teeth were scanned in the four primary stages of the endodontic procedure—before treatment and after shaping, filling and retreatment. Forty-eight models were accomplished, images were analyzed, and the region growing algorithm was seeded to achieve fast and precise segmentation of the canal space. The segmentation was successful in all specimens.