Deep learning-based image reconstruction and post-processing methods in positron emission tomography for low-dose imaging and resolution enhancement
Image processing plays a crucial role in maximising diagnostic quality of positron emission
tomography (PET) images. Recently, deep learning methods developed across many fields …
tomography (PET) images. Recently, deep learning methods developed across many fields …
[HTML][HTML] [18F] FDG-PET/CT radiomics and artificial intelligence in lung cancer: technical aspects and potential clinical applications
R Manafi-Farid, E Askari, I Shiri, C Pirich… - Seminars in nuclear …, 2022 - Elsevier
Lung cancer is the second most common cancer and the leading cause of cancer-related
death worldwide. Molecular imaging using [18 F] fluorodeoxyglucose Positron Emission …
death worldwide. Molecular imaging using [18 F] fluorodeoxyglucose Positron Emission …
A survey of deep learning approaches to image restoration
In this paper, we present an extensive review on deep learning methods for image
restoration tasks. Deep learning techniques, led by convolutional neural networks, have …
restoration tasks. Deep learning techniques, led by convolutional neural networks, have …
Adaptive rectification based adversarial network with spectrum constraint for high-quality PET image synthesis
Positron emission tomography (PET) is a typical nuclear imaging technique, which can
provide crucial functional information for early brain disease diagnosis. Generally, clinically …
provide crucial functional information for early brain disease diagnosis. Generally, clinically …
A review on AI in PET imaging
K Matsubara, M Ibaraki, M Nemoto, H Watabe… - Annals of Nuclear …, 2022 - Springer
Artificial intelligence (AI) has been applied to various medical imaging tasks, such as
computer-aided diagnosis. Specifically, deep learning techniques such as convolutional …
computer-aided diagnosis. Specifically, deep learning techniques such as convolutional …
Parametric image generation with the uEXPLORER total-body PET/CT system through deep learning
Purpose Total-body dynamic positron emission tomography/computed tomography
(PET/CT) provides much sensitivity for clinical imaging and research, bringing new …
(PET/CT) provides much sensitivity for clinical imaging and research, bringing new …
[HTML][HTML] Pix2Pix generative adversarial network for low dose myocardial perfusion SPECT denoising
Background Myocardial perfusion (MP) SPECT is a well-established method for diagnosing
cardiac disease, yet its radiation risk poses safety concern. This study aims to apply and …
cardiac disease, yet its radiation risk poses safety concern. This study aims to apply and …
Image enhancement of whole-body oncology [18F]-FDG PET scans using deep neural networks to reduce noise
A Mehranian, SD Wollenweber, MD Walker… - European journal of …, 2022 - Springer
Purpose To enhance the image quality of oncology [18F]-FDG PET scans acquired in
shorter times and reconstructed by faster algorithms using deep neural networks. Methods …
shorter times and reconstructed by faster algorithms using deep neural networks. Methods …
Artificial intelligence-based PET denoising could allow a two-fold reduction in [18F]FDG PET acquisition time in digital PET/CT
Purpose We investigated whether artificial intelligence (AI)-based denoising halves PET
acquisition time in digital PET/CT. Methods One hundred ninety-five patients referred for …
acquisition time in digital PET/CT. Methods One hundred ninety-five patients referred for …
A personalized deep learning denoising strategy for low-count PET images
Objective. Deep learning denoising networks are typically trained with images that are
representative of the testing data. Due to the large variability of the noise levels in positron …
representative of the testing data. Due to the large variability of the noise levels in positron …