A review on medical imaging synthesis using deep learning and its clinical applications
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 …
clinical application. Specifically, we summarized the recent developments of deep learning …
A review of deep learning based methods for medical image multi-organ segmentation
Deep learning has revolutionized image processing and achieved the-state-of-art
performance in many medical image segmentation tasks. Many deep learning-based …
performance in many medical image segmentation tasks. Many deep learning-based …
MRI‐only based synthetic CT generation using dense cycle consistent generative adversarial networks
Purpose Automated synthetic computed tomography (sCT) generation based on magnetic
resonance imaging (MRI) images would allow for MRI‐only based treatment planning in …
resonance imaging (MRI) images would allow for MRI‐only based treatment planning in …
Hybrid total-body pet scanners—current status and future perspectives
Purpose Since the 1990s, PET has been successfully combined with MR or CT systems. In
the past years, especially PET systems have seen a trend towards an enlarged axial field of …
the past years, especially PET systems have seen a trend towards an enlarged axial field of …
Deep learning-based attenuation correction in the absence of structural information for whole-body positron emission tomography imaging
Deriving accurate structural maps for attenuation correction (AC) of whole-body positron
emission tomography (PET) remains challenging. Common problems include truncation …
emission tomography (PET) remains challenging. Common problems include truncation …
Synthetic CT generation from non-attenuation corrected PET images for whole-body PET imaging
Attenuation correction (AC) of PET/MRI faces challenges including inter-scan motion, image
artifacts such as truncation and distortion, and erroneous transformation of structural voxel …
artifacts such as truncation and distortion, and erroneous transformation of structural voxel …
Whole-body PET estimation from low count statistics using cycle-consistent generative adversarial networks
Lowering either the administered activity or scan time is desirable in PET imaging as it
decreases the patient's radiation burden or improves patient comfort and reduces motion …
decreases the patient's radiation burden or improves patient comfort and reduces motion …
Machine learning in quantitative PET: A review of attenuation correction and low-count image reconstruction methods
The rapid expansion of machine learning is offering a new wave of opportunities for nuclear
medicine. This paper reviews applications of machine learning for the study of attenuation …
medicine. This paper reviews applications of machine learning for the study of attenuation …
MRI-based treatment planning for proton radiotherapy: dosimetric validation of a deep learning-based liver synthetic CT generation method
Magnetic resonance imaging (MRI) has been widely used in combination with computed
tomography (CT) radiation therapy because MRI improves the accuracy and reliability of …
tomography (CT) radiation therapy because MRI improves the accuracy and reliability of …
Evaluation of a deep learning-based pelvic synthetic CT generation technique for MRI-based prostate proton treatment planning
The purpose of this work is to validate the application of a deep learning-based method for
pelvic synthetic CT (sCT) generation that can be used for prostate proton beam therapy …
pelvic synthetic CT (sCT) generation that can be used for prostate proton beam therapy …