4.7 Article

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

Related references

Note: Only part of the references are listed.
Article Cardiac & Cardiovascular Systems

Standard SPECT myocardial perfusion estimation from half-time acquisitions using deep convolutional residual neural networks

Isaac Shiri et al.

Summary: This study aimed to assess the feasibility of reducing acquisition time in MPI-SPECT imaging using deep learning techniques. The results showed that predicted full time images had better quality than predicted full projections, with significant increase in error metrics when reducing acquisition time per projection. The deep neural network effectively recovered image quality and reduced bias in quantification metrics.

JOURNAL OF NUCLEAR CARDIOLOGY (2021)

Article Radiology, Nuclear Medicine & Medical Imaging

Whole-body voxel-based internal dosimetry using deep learning

Azadeh Akhavanallaf et al.

Summary: In the era of precision medicine, a novel method utilizing deep learning algorithms for whole-body personalized organ-level dosimetry has been proposed, showing comparable performance to Monte Carlo simulations and overcoming limitations of conventional dosimetry techniques in nuclear medicine.

EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING (2021)

Article Radiology, Nuclear Medicine & Medical Imaging

Projection Space Implementation of Deep Learning-Guided Low-Dose Brain PET Imaging Improves Performance over Implementation in Image Space

Amirhossein Sanaat et al.

JOURNAL OF NUCLEAR MEDICINE (2020)

Article Radiology, Nuclear Medicine & Medical Imaging

Spatially guided nonlocal mean approach for denoising of PET images

Hossein Arabi et al.

MEDICAL PHYSICS (2020)

Review Radiology, Nuclear Medicine & Medical Imaging

Preparing Medical Imaging Data for Machine Learning

Martin J. Willemink et al.

RADIOLOGY (2020)

Article Radiology, Nuclear Medicine & Medical Imaging

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

Isaac Shiri et al.

EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING (2020)

Article Computer Science, Artificial Intelligence

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

Long Zhou et al.

MEDICAL IMAGE ANALYSIS (2020)

Review Radiology, Nuclear Medicine & Medical Imaging

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

Hossein Arabi et al.

EUROPEAN JOURNAL OF HYBRID IMAGING (2020)

Proceedings Paper Engineering, Biomedical

Low dose PET imaging with CT-aided cycle-consistent adversarial networks

Yang Lei et al.

MEDICAL IMAGING 2020: PHYSICS OF MEDICAL IMAGING (2020)

Article Radiology, Nuclear Medicine & Medical Imaging

Low dose positron emission tomography emulation from decimated high statistics: A clinical validation study

Josh Schaefferkoetter et al.

MEDICAL PHYSICS (2019)

Article Radiology, Nuclear Medicine & Medical Imaging

Ultra-low-dose PET reconstruction using generative adversarial network with feature matching and task-specific perceptual loss

Jiahong Ouyang et al.

MEDICAL PHYSICS (2019)

Article Radiology, Nuclear Medicine & Medical Imaging

Novel adversarial semantic structure deep learning for MRI-guided attenuation correction in brain PET/MRI

Hossein Arabi et al.

EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING (2019)

Article Computer Science, Interdisciplinary Applications

3D Auto-Context-Based Locality Adaptive Multi-Modality GANs for PET Synthesis

Yan Wang et al.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2019)

Article Engineering, Biomedical

An investigation of quantitative accuracy for deep learning based denoising in oncological PET

Wenzhuo Lu et al.

PHYSICS IN MEDICINE AND BIOLOGY (2019)

Article Radiology, Nuclear Medicine & Medical Imaging

PET image denoising using unsupervised deep learning

Jianan Cui et al.

EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING (2019)

Article Engineering, Biomedical

Whole-body PET estimation from low count statistics using cycle-consistent generative adversarial networks

Yang Lei et al.

PHYSICS IN MEDICINE AND BIOLOGY (2019)

Article Radiology, Nuclear Medicine & Medical Imaging

Full-Dose PET Image Estimation from Low-Dose PET Image Using Deep Learning: a Pilot Study

Sydney Kaplan et al.

JOURNAL OF DIGITAL IMAGING (2019)

Article Radiology, Nuclear Medicine & Medical Imaging

Ultra-Low-Dose 18F-Florbetaben Amyloid PET Imaging Using Deep Learning with Multi-Contrast MRI Inputs

Kevin T. Chen et al.

RADIOLOGY (2019)

Article Radiology, Nuclear Medicine & Medical Imaging

PET Image Denoising Using a Deep Neural Network Through Fine Tuning

Kuang Gong et al.

IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES (2019)

Review Radiology, Nuclear Medicine & Medical Imaging

Towards enhanced PET quantification in clinical oncology

Habib Zaidi et al.

BRITISH JOURNAL OF RADIOLOGY (2018)

Article Computer Science, Artificial Intelligence

Joint solution for PET image segmentation, denoising, and partial volume correction

Ziyue Xu et al.

MEDICAL IMAGE ANALYSIS (2018)

Article Engineering, Biomedical

Improvement of image quality in PET using post-reconstruction hybrid spatial-frequency domain filtering

Hossein Arabi et al.

PHYSICS IN MEDICINE AND BIOLOGY (2018)

Article Computer Science, Artificial Intelligence

A survey on deep learning in medical image analysis

Geert Litjens et al.

MEDICAL IMAGE ANALYSIS (2017)

Article Computer Science, Interdisciplinary Applications

Postreconstruction Nonlocal Means Filtering of Whole-Body PET With an Anatomical Prior

Chung Chan et al.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2014)

Article Radiology, Nuclear Medicine & Medical Imaging

Standards for PET Image Acquisition and Quantitative Data Analysis

Ronald Boellaard

JOURNAL OF NUCLEAR MEDICINE (2009)