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3D helical CT Reconstruction with a Memory Efficient Learned Primal-Dual Architecture
To the best of our knowledge, this work is the first to apply an unrolled deep learning architecture for reconstruction on full-sized clinical data, like those in the Low dose CT image and projection data set (LDCT).
Invertible Learned Primal-Dual
We propose invertible Learned Primal-Dual as a method for tomographic image reconstruction.
Deep learning based dictionary learning and tomographic image reconstruction
This work presents an approach for image reconstruction in clinical low-dose tomography that combines principles from sparse signal processing with ideas from deep learning.
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