[HTML][HTML] Deep learning based synthesis of MRI, CT and PET: Review and analysis

S Dayarathna, KT Islam, S Uribe, G Yang, M Hayat… - Medical image …, 2024 - Elsevier
Medical image synthesis represents a critical area of research in clinical decision-making,
aiming to overcome the challenges associated with acquiring multiple image modalities for …

A review on medical imaging synthesis using deep learning and its clinical applications

T Wang, Y Lei, Y Fu, JF Wynne… - Journal of applied …, 2021 - Wiley Online Library
This paper reviewed the deep learning‐based studies for medical imaging synthesis and its
clinical application. Specifically, we summarized the recent developments of deep learning …

[HTML][HTML] The promise of artificial intelligence and deep learning in PET and SPECT imaging

H Arabi, A AkhavanAllaf, A Sanaat, I Shiri, H Zaidi - Physica Medica, 2021 - Elsevier
This review sets out to discuss the foremost applications of artificial intelligence (AI),
particularly deep learning (DL) algorithms, in single-photon emission computed tomography …

Applications of artificial intelligence and deep learning in molecular imaging and radiotherapy

H Arabi, H Zaidi - European Journal of Hybrid Imaging, 2020 - Springer
This brief review summarizes the major applications of artificial intelligence (AI), in particular
deep learning approaches, in molecular imaging and radiation therapy research. To this …

Deep learning-assisted ultra-fast/low-dose whole-body PET/CT imaging

A Sanaat, I Shiri, H Arabi, I Mainta, R Nkoulou… - European journal of …, 2021 - Springer
Purpose Tendency is to moderate the injected activity and/or reduce acquisition time in PET
examinations to minimize potential radiation hazards and increase patient comfort. This …

Deep learning-based image reconstruction and post-processing methods in positron emission tomography for low-dose imaging and resolution enhancement

CD Pain, GF Egan, Z Chen - European Journal of Nuclear Medicine and …, 2022 - Springer
Image processing plays a crucial role in maximising diagnostic quality of positron emission
tomography (PET) images. Recently, deep learning methods developed across many fields …

Ultra-low-dose chest CT imaging of COVID-19 patients using a deep residual neural network

I Shiri, A Akhavanallaf, A Sanaat, Y Salimi, D Askari… - European …, 2021 - Springer
Objectives The current study aimed to design an ultra-low-dose CT examination protocol
using a deep learning approach suitable for clinical diagnosis of COVID-19 patients …

Deep-JASC: joint attenuation and scatter correction in whole-body 18F-FDG PET using a deep residual network

I Shiri, H Arabi, P Geramifar, G Hajianfar… - European journal of …, 2020 - Springer
Objective We demonstrate the feasibility of direct generation of attenuation and scatter-
corrected images from uncorrected images (PET-nonASC) using deep residual networks in …

Whole-body voxel-based internal dosimetry using deep learning

A Akhavanallaf, I Shiri, H Arabi, H Zaidi - European Journal of Nuclear …, 2021 - Springer
Purpose In the era of precision medicine, patient-specific dose calculation using Monte
Carlo (MC) simulations is deemed the gold standard technique for risk-benefit analysis of …

Deep learning–based denoising of low-dose SPECT myocardial perfusion images: quantitative assessment and clinical performance

N Aghakhan Olia, A Kamali-Asl, S Hariri Tabrizi… - European journal of …, 2022 - Springer
Purpose This work was set out to investigate the feasibility of dose reduction in SPECT
myocardial perfusion imaging (MPI) without sacrificing diagnostic accuracy. A deep learning …