Assessment of image quality and diagnostic accuracy for cervical spondylosis using T2w-STIR sequence with a deep learning-based reconstruction approach.

Qiuying Tao Kaiyu Wang Baohong Wen Yimeng Kang Jinghan Dang Jieping Sun Xiaoyu Niu Mengzhe Zhang Zijun Liu Weijian Wang Yong Zhang Jingliang Cheng

Published in: European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society (2024)

Our investigation establishes that 3.0 T fast MRI images subjected to DLR processing present heightened image quality, bolstered diagnostic performance, and reduced scanning durations for cervical spine MRI compared with conventional sequences.

Keyphrases

image quality
deep learning
computed tomography
contrast enhanced
magnetic resonance imaging
dual energy
convolutional neural network
diffusion weighted imaging
artificial intelligence
machine learning
optical coherence tomography
magnetic resonance
mass spectrometry
electron microscopy
genetic diversity