CT Image Denoising and Deblurring With Deep Learning: Current Status and Perspectives
Yiming Lei, Chuang Niu, Junping Zhang, Ge Wang, Hongming Shan
Abstract
This article reviews the deep learning methods for computed tomography image denoising and deblurring separately and simultaneously. Then, we discuss promising directions in this field, such as a combination with large-scale pretrained models and large language models. Currently, deep learning is revolutionizing medical imaging in a data-driven manner. With rapidly evolving learning paradigms, related algorithms and models are making rapid progress toward clinical applications.
Topics & Concepts
DeblurringDeep learningArtificial intelligenceComputer scienceField (mathematics)Image (mathematics)Computed tomographyNoise reductionMachine learningImage restorationImage processingRadiologyMedicineMathematicsPure mathematicsImage and Signal Denoising MethodsMedical Imaging Techniques and ApplicationsSeismic Imaging and Inversion Techniques