Browsing Department of Computational and Data Sciences (CDS) by Subject "MRI"
Now showing items 1-2 of 2
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Development of Novel Deep Learning Methods for Fast-MRI: Anatomical Image Reconstruction to Quantitative Imaging
In medical imaging, the task of estimating interpretable anatomical images from raw scanner data - based on underlying physical principles - is known as an "inverse problem". The solution to such inverse problems can be ... -
Development of Novel Deep Learning Models for Quantitative Medical Image Analysis
Medical imaging provides a non-invasive way to visualize tissues and diseases, enabling both qualitative and quantitative assessments that are needed in diagnosing and monitoring a wide range of conditions. Modalities ...