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Found 5 papers, 0 papers with code
A Data-Driven Reconstruction Technique based on Newton's Method for Emission Tomography
In this work, we present the Deep Newton Reconstruction Network (DNR-Net), a hybrid data-driven reconstruction technique for emission tomography inspired by Newton's method, a well-known iterative optimization algorithm.
A Bayesian Optimization Approach for Attenuation Correction in SPECT Brain Imaging
Photon attenuation and scatter are the two main physical factors affecting the diagnostic quality of SPECT in its applications in brain imaging.
Deep Convolutional Neural Network for Low Projection SPECT Imaging Reconstruction
In this paper, we present a novel method for tomographic image reconstruction in SPECT imaging with a low number of projections.
SPECT Angle Interpolation Based on Deep Learning Methodologies
For evaluation of the efficacy of the method, phantoms based on Shepp Logan, with various noise levels added were used, and the resulting interpolated sinograms are reconstructed using Ordered Subset Expectation Maximization (OSEM) and compared to the reconstructions of the original sinograms.
SPECT Imaging Reconstruction Method Based on Deep Convolutional Neural Network
In this paper, we explore a novel method for tomographic image reconstruction in the field of SPECT imaging.
