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Tomography, Volume 10, Issue 4
April 2024 - 15 articles
Cover Story: Diffusion tensor imaging (DTI) offers insights into tissue microstructure and microarchitecture within a voxel. In the context of the physeal–metaphyseal complex, DTI facilitates pediatric growth prediction and evaluation. However, achieving accurate DTI metrics requires optimal acquisition parameters and satisfactory SNRs. While deep learning (DL) has enhanced DTI in the central nervous system and skeletal muscle, its application to the human growth plate remains unexplored. Our study pioneers the use of a DL denoising algorithm on DTI data of the knee growth plate. By assessing its impact on microstructural diffusion metrics, we aim to enhance spatial resolution and provide reliable insights into growth plate changes over time. View this paper
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Tomography - ISSN 2379-139XCreative Common CC BY license