Application of deep learning–based image reconstruction in MRI of the temporomandibular joint to improve image quality and reduce scan time

Motivation: MRI examination of temporomandibular joint takes a long time to scan, especially when scanning in the open-mouth position, the patient cannot maintain the open-mouth state for a long time, it is easy to cause movements of the temporomandibular joint, resulting in motion artifacts in the scanned image and failure of the examination. On the premise of ensuring image quality, it is particularly important to reduce scan time. Goal(s): Applying deep learning reconstruction to improve temporomandibular joint MRI image quality and reduce scanning time. Approach: clinical experiments. Results: Deep learning reconstruction can improve image quality and significantly shorten scanning time of temporomandibular joint MRI. Impact: Deep learning reconstruction can significantly shorten scan time while improving image quality, helping radiologists to diagnose quickly and confidently，helping patients to spend less time feeling anxious in an MRI and more time living their life.