Effect of data size on tooth numbering performance via artificial intelligence using panoramic radiographs.

Journal: Oral radiology

PMID: 37405624

Abstract

OBJECTIVE: This study aims to investigate the effect of number of data on model performance, for the detection of tooth numbering problem on dental panoramic radiographs, with the help of image processing and deep learning algorithms.

Authors

Semih Gülüm

AVL Research and Engineering, Abdurrahmangazi Mah. Ataturk Cad. No: 22 11/22 Kat: 6 Sultanbeyli, Istanbul, 34920, Turkey.
Seçilay Kutal

AREAL.ai, San Francisco, USA.
Kader Cesur Aydin

School of Dentistry, Head of Department Dentomaxillofacial Radiology, Istanbul Medipol University, Ataturk Bulvarı No: 27 Unkapanı, Istanbul, 34083, Turkey. kadercesur@yahoo.com.
Gazi Akgun

Department of Mechatronics Engineering, Marmara University, Istanbul 34744, Turkey.
Aleyna Akdağ

School of Dentistry, Istanbul Medipol University, Goztepe Mah, Ataturk Cad, Beykoz, Istanbul, 34810, Turkey.

Keywords

Adult Algorithms Artificial Intelligence Humans Image Processing, Computer-Assisted Radiography, Panoramic Tooth

External Resources

View on PubMed Access via DOI PubMed (37405624)

Effect of data size on tooth numbering performance via artificial intelligence using panoramic radiographs.

Abstract

Authors

Keywords

External Resources

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