11 citations · 13 across the 5 of their papers we have counts for
9 papers
Classification of Influenza Hemagglutinin Protein Sequences using Convolutional Neural Networks
Charalambos Chrysostomou, Floris Alexandrou, Mihalis A. Nicolaou +1
The Influenza virus can be considered as one of the most severe viruses that can infect multiple species with often fatal consequences to the hosts. The Hemagglutinin (HA) gene of…
Sinogram Denoise Based on Generative Adversarial Networks
Charalambos Chrysostomou
A novel method for sinogram denoise based on Generative Adversarial Networks (GANs) in the field of SPECT imaging is presented. Projection data from software phantoms were used to…
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…
Prediction of Influenza A virus infections in humans using an Artificial Neural Network learning approach
Charalambos Chrysostomou, Harris Partaourides, Huseyin Seker
The Influenza type A virus can be considered as one of the most severe viruses that can infect multiple species with often fatal consequences to the hosts. The Haemagglutinin (HA)…
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…