Weekley, D. M., & McPherson-Duckworth, J. A., & Sukhanova, A., & Jana, A. (2025, March), Evaluating the Suitability of Different Intraoral Scan Resolutions for Deep Learning-Based Tooth Segmentation  Paper presented at 2025 ASEE North Central Section  (NCS) Annual Conference, Marshall University, Huntington, West Virginia. 10.18260/1-2--54664

\bibitem{asee_peer_54664}
  Weekley, D. M., \& McPherson-Duckworth, J. A., \& Sukhanova, A., \& Jana, A. (2025, March), \emph{Evaluating the Suitability of Different Intraoral Scan Resolutions for Deep Learning-Based Tooth Segmentation}
  Paper presented at 2025 ASEE North Central Section  (NCS) Annual Conference, Marshall University, Huntington, West Virginia.
  10.18260/1-2--54664

Daron Marshall Weekley, Jace A McPherson-Duckworth, Anastasiia Sukhanova, and Ananya Jana.  "Evaluating the Suitability of Different Intraoral Scan Resolutions for Deep Learning-Based Tooth Segmentation".  2025 ASEE North Central Section  (NCS) Annual Conference, Marshall University, Huntington, West Virginia, 2025, March.  ASEE Conferences, 2025.  https://peer.asee.org/54664 Internet.  16 May, 2025

\bibitem{asee_peer_54664}
  Daron Marshall Weekley, Jace A McPherson-Duckworth, Anastasiia Sukhanova, and Ananya Jana.
  "Evaluating the Suitability of Different Intraoral Scan Resolutions for Deep Learning-Based Tooth Segmentation".
  \emph{2025 ASEE North Central Section  (NCS) Annual Conference, Marshall University, Huntington, West Virginia, 2025, March}.
  ASEE Conferences, 2025.
  https://peer.asee.org/54664 Internet.  16 May, 2025

@INPROCEEDINGS{asee_peer_54664
author = "Daron Marshall Weekley, Jace A McPherson-Duckworth, Anastasiia Sukhanova, and Ananya Jana"
title = "Evaluating the Suitability of Different Intraoral Scan Resolutions for Deep Learning-Based Tooth Segmentation"
booktitle = "2025 ASEE North Central Section  (NCS) Annual Conference"
year = "2025"
month = "March"
address = "Marshall University, Huntington, West Virginia"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/54664}
number = {10.18260/1-2--54664}
}

TY  - CPAPER
AB  - Tooth landmark localization is an important task in computer-aided orthodontics. Accurate estimation of the locations of the tooth landmarks is crucial for various dental applications, and dental research. Manually annotating the tooth landmarks is a time-consuming task and it can be extremely tedious. Currently, there is limited research on the task of automatic tooth landmark localization. In this work we propose a deep learning-based approach to automatically predict the  tooth landmarks from intraoral scans. We perform the experiments on the recently available dataset called 3DTeethLand.
AU  - Daron Marshall Weekley
AU  - Jace A McPherson-Duckworth
AU  - Anastasiia Sukhanova
AU  - Ananya Jana
CY  - Marshall University, Huntington, West Virginia
DA  - 2025/03/28
PB  - ASEE Conferences
TI  - Evaluating the Suitability of Different Intraoral Scan Resolutions for Deep Learning-Based Tooth Segmentation
UR  - https://peer.asee.org/54664
DO  - 10.18260/1-2--54664
ER  -