13 citations · 15 across the 5 of their papers we have counts for
8 papers
A Data-Driven Reconstruction Technique based on Newton's Method for Emission Tomography
Loizos Koutsantonis, Tiago Carneiro, Emmanuel Kieffer +2
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…
A Bayesian Optimization Approach for Attenuation Correction in SPECT Brain Imaging
Loizos Koutsantonis, Ayman Makki, Tiago Carneiro +2
Photon attenuation and scatter are the two main physical factors affecting the diagnostic quality of SPECT in its applications in brain imaging. In this work, we present a novel Ba…
Deep Convolutional Neural Network for Low Projection SPECT Imaging Reconstruction
Charalambos Chrysostomou, Loizos Koutsantonis, Christos Lemesios +1
In this paper, we present a novel method for tomographic image reconstruction in SPECT imaging with a low number of projections. Deep convolutional neural networks (CNN) are employ…
SPECT Angle Interpolation Based on Deep Learning Methodologies
Charalambos Chrysostomou, Loizos Koutsantonis, Christos Lemesios +1
A novel method for SPECT angle interpolation based on deep learning methodologies is presented. Projection data from software phantoms were used to train the proposed model. For ev…
SPECT Imaging Reconstruction Method Based on Deep Convolutional Neural Network
Charalambos Chrysostomou, Loizos Koutsantonis, Christos Lemesios +1
In this paper, we explore a novel method for tomographic image reconstruction in the field of SPECT imaging. Deep Learning methodologies and more specifically deep convolutional ne…
Attributing Uncertainties in the Identification of Hotspots in SPECT Imaging
Costas N. Papanicolas, Loizos Koutsantonis, Efstathios Stiliaris
In SPECT imaging, the identification and detection of a lesion rely either on visual inspection of the reconstructed tomographic images or post-processing image analysis methods. B…