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Abstract #2934

On Training Model Bias of Deep Learning based Super-resolution Frameworks for Magnetic Resonance Imaging

Mamata Shrestha1, Nian Wang2,3, and Ukash Nakarmi1
1Computer Science and Computer Engineering, University of Arkansas, Fayetteville, AR, United States, 2Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, United States, 3Stark Neurosciences Research Institute, Indianapolis, IN, United States

Synopsis

Keywords: Image Reconstruction, Data Processing, Image super-resolution, model bias, deep learningDeep Learning based image super-resolution methods are biased towards training data modeling. Generalizability of DL based super-resolution frameworks can be improved by introducing variability and diversity in the training data.

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Keywords