Medical image segmentation based on U-net: A review.

G Du, X Cao, J Liang, X Chen… - Journal of Imaging …, 2020‏ - search.ebscohost.com
Medical image analysis is performed by analyzing images obtained by medical imaging
systems to solve clinical problems. The purpose is to extract effective information and …

Radiological images and machine learning: trends, perspectives, and prospects

Z Zhang, E Sejdić - Computers in biology and medicine, 2019‏ - Elsevier
The application of machine learning to radiological images is an increasingly active
research area that is expected to grow in the next five to ten years. Recent advances in …

3D conditional generative adversarial networks for high-quality PET image estimation at low dose

Y Wang, B Yu, L Wang, C Zu, DS Lalush, W Lin, X Wu… - Neuroimage, 2018‏ - Elsevier
Positron emission tomography (PET) is a widely used imaging modality, providing insight
into both the biochemical and physiological processes of human body. Usually, a full dose …

Multi-modality cascaded convolutional neural networks for Alzheimer's disease diagnosis

M Liu, D Cheng, K Wang, Y Wang… - Neuroinformatics, 2018‏ - Springer
Accurate and early diagnosis of Alzheimer's disease (AD) plays important role for patient
care and development of future treatment. Structural and functional neuroimages, such as …

Supervised learning with cyclegan for low-dose FDG PET image denoising

L Zhou, JD Schaefferkoetter, IWK Tham, G Huang… - Medical image …, 2020‏ - Elsevier
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 …

Deep auto-context convolutional neural networks for standard-dose PET image estimation from low-dose PET/MRI

L **ang, Y Qiao, D Nie, L An, W Lin, Q Wang, D Shen - Neurocomputing, 2017‏ - Elsevier
Positron emission tomography (PET) is an essential technique in many clinical applications
such as tumor detection and brain disorder diagnosis. In order to obtain high-quality PET …

Adaptive rectification based adversarial network with spectrum constraint for high-quality PET image synthesis

Y Luo, L Zhou, B Zhan, Y Fei, J Zhou, Y Wang… - Medical Image …, 2022‏ - Elsevier
Positron emission tomography (PET) is a typical nuclear imaging technique, which can
provide crucial functional information for early brain disease diagnosis. Generally, clinically …

Review and prospect: artificial intelligence in advanced medical imaging

S Wang, G Cao, Y Wang, S Liao, Q Wang, J Shi… - Frontiers in …, 2021‏ - frontiersin.org
Artificial intelligence (AI) as an emerging technology is gaining momentum in medical
imaging. Recently, deep learning-based AI techniques have been actively investigated in …

3D auto-context-based locality adaptive multi-modality GANs for PET synthesis

Y Wang, L Zhou, B Yu, L Wang, C Zu… - IEEE transactions on …, 2018‏ - ieeexplore.ieee.org
Positron emission tomography (PET) has been substantially used recently. To minimize the
potential health risk caused by the tracer radiation inherent to PET scans, it is of great …

200x low-dose PET reconstruction using deep learning

J Xu, E Gong, J Pauly, G Zaharchuk - arxiv preprint arxiv:1712.04119, 2017‏ - arxiv.org
Positron emission tomography (PET) is widely used in various clinical applications,
including cancer diagnosis, heart disease and neuro disorders. The use of radioactive tracer …