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Abstract #1968

Usefulness of Super-Resolution Deep Learning-Based Reconstruction on High-Resolution 3D T2WI for Evaluation of the Internal Auditory Canal

Hiroyuki Uetani1, Takeshi Nakaura1, Koya Iwashita1, Kosuke Morita2, Yuichi Yamashita3, Takumi Saito3, Kensei Matsuo2, and Toshinori Hirai1
1Diagnostic Radiology, Kumamoto university, Kumamoto, Japan, 2Central Radiology section, Kumamoto University Hospital, Kumamoto, Japan, 3MRI sales department, sales engineer group, Canon Medical Systems Corporation, Kawasaki, Japan

Synopsis

Keywords: AI/ML Image Reconstruction, Image Reconstruction, deep learning; internal auditory canal; high resolution T2-weighted imaging; super-resolution.

Motivation: There are no reports on the usefulness of high-resolution three-dimensional T2-weighted imaging (HR-3D T2WI) using super-resolution deep learning-based reconstruction (SR-DLR) technique.

Goal(s): We aimed to determine whether a novel SR-DLR technique can improve the image quality of HR-3D T2WI for assessing the IAC and inner ear.

Approach: We qualitatively assessed the image quality of HR-3D T2WI with and without SR-DLR for the visualization of detailed structures of the IAC and inner ear.

Results: SR-DLR was shown to significantly improve the image quality of HR-3D T2WI in visualizing nerves in the IAC and inner ear compared to conventional HR-3D T2WI without SR-DLR.

Impact: High-resolution three-dimensional T2-weighted imaging with super-resolution deep learning-based reconstruction can improve the visualization of detailed structures of the internal auditory canal and inner ear without extended acquisition time.

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Keywords