Deep learning for tomographic image reconstruction
Deep-learning-based tomographic imaging is an important application of artificial
intelligence and a new frontier of machine learning. Deep learning has been widely used in …
intelligence and a new frontier of machine learning. Deep learning has been widely used in …
Introduction to radiomics
Radiomics is a rapidly evolving field of research concerned with the extraction of quantitative
metrics—the so-called radiomic features—within medical images. Radiomic features capture …
metrics—the so-called radiomic features—within medical images. Radiomic features capture …
Deep learning for PET image reconstruction
This article reviews the use of a subdiscipline of artificial intelligence (AI), deep learning, for
the reconstruction of images in positron emission tomography (PET). Deep learning can be …
the reconstruction of images in positron emission tomography (PET). Deep learning can be …
Supervised learning with cyclegan for low-dose FDG PET image denoising
PET imaging involves radiotracer injections, raising concerns about the risk of radiation
exposure. To minimize the potential risk, one way is to reduce the injected tracer. However …
exposure. To minimize the potential risk, one way is to reduce the injected tracer. However …
Applications of artificial intelligence and deep learning in molecular imaging and radiotherapy
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 approaches, in molecular imaging and radiation therapy research. To this …
Using deep learning techniques in medical imaging: a systematic review of applications on CT and PET
I Domingues, G Pereira, P Martins, H Duarte… - Artificial Intelligence …, 2020 - Springer
Medical imaging is a rich source of invaluable information necessary for clinical judgements.
However, the analysis of those exams is not a trivial assignment. In recent times, the use of …
However, the analysis of those exams is not a trivial assignment. In recent times, the use of …
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 …
Model-based deep learning PET image reconstruction using forward–backward splitting expectation–maximization
A Mehranian, AJ Reader - IEEE transactions on radiation and …, 2020 - ieeexplore.ieee.org
We propose a forward-backward splitting algorithm to integrate deep learning into maximum-
a-posteriori (MAP) positron emission tomography (PET) image reconstruction. The MAP …
a-posteriori (MAP) positron emission tomography (PET) image reconstruction. The MAP …
Subsecond total-body imaging using ultrasensitive positron emission tomography
A 194-cm-long total-body positron emission tomography/computed tomography (PET/CT)
scanner (uEXPLORER), has been constructed to offer a transformative platform for human …
scanner (uEXPLORER), has been constructed to offer a transformative platform for human …
DPIR-Net: Direct PET image reconstruction based on the Wasserstein generative adversarial network
Positron emission tomography (PET) is an advanced medical imaging technique widely
used in various clinical applications, such as tumor detection and neurologic disorders …
used in various clinical applications, such as tumor detection and neurologic disorders …