Magnetic resonance image generation using enhanced TransUNet in temporomandibular disorder patients.

Journal: Dento maxillo facial radiology
Published Date: Jul 1, 2025

Abstract

OBJECTIVES: Temporomandibular disorder (TMD) patients experience a variety of clinical symptoms, and MRI is the most effective tool for diagnosing temporomandibular joint (TMJ) disc displacement. This study aimed to develop a transformer-based deep learning model to generate T2-weighted (T2w) images from proton density-weighted (PDw) images, reducing MRI scan time for TMD patients.

Authors

  • Eun-Gyu Ha
    Department of Oral and Maxillofacial Radiology, Yonsei University College of Dentistry, 50-1 Yonsei-ro Seodaemun-gu, Seoul, 03722, Korea.
  • Kug Jin Jeon
    Department of Oral and Maxillofacial Radiology, Yonsei University College of Dentistry, Seoul, Republic of Korea.
  • Chena Lee
    Department of Oral and Maxillofacial Radiology, Yonsei University College of Dentistry, Seoul, Republic of Korea.
  • Dong-Hyun Kim
    Neurobiota Research Center, College of Pharmacy, Kyung Hee University, Dongdaemun-gu, Seoul 02447, Republic of Korea.
  • Sang-Sun Han
    Department of Oral and Maxillofacial Radiology, Yonsei University College of Dentistry, Seoul, Republic of Korea. Electronic address: sshan@yuhs.ac.

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