AIMC Topic: Positron-Emission Tomography
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Deep learning-based PET image denoising and reconstruction: a review.
Radiological physics and technology
Feb 6, 2024
This review focuses on positron emission tomography (PET) imaging algorithms and traces the evolution of PET image reconstruction methods. First, we provide an overview of conventional PET image reconstruction methods from filtered backprojection thr...
Strategies for deep learning-based attenuation and scatter correction of brain F-FDG PET images in the image domain.
Medical physics
Jan 10, 2024
BACKGROUND: Attenuation and scatter correction is crucial for quantitative positron emission tomography (PET) imaging. Direct attenuation correction (AC) in the image domain using deep learning approaches has been recently proposed for combined PET/M...
Comparison of deep learning networks for fully automated head and neck tumor delineation on multi-centric PET/CT images.
Radiation oncology (London, England)
Jan 8, 2024
OBJECTIVES: Deep learning-based auto-segmentation of head and neck cancer (HNC) tumors is expected to have better reproducibility than manual delineation. Positron emission tomography (PET) and computed tomography (CT) are commonly used in tumor segm...
Machine and deep learning models for accurate detection of ischemia and scar with myocardial blood flow positron emission tomography imaging.
Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
Jan 5, 2024
BACKGROUND: Quantification of myocardial blood flow (MBF) is used for the noninvasive diagnosis of patients with coronary artery disease (CAD). This study compared traditional statistics, machine learning, and deep learning techniques in their abilit...
Artificial Intelligence for PET and SPECT Image Enhancement.
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Jan 2, 2024
Nuclear medicine imaging modalities such as PET and SPECT are confounded by high noise levels and low spatial resolution, necessitating postreconstruction image enhancement to improve their quality and quantitative accuracy. Artificial intelligence (...
Deep Generalized Learning Model for PET Image Reconstruction.
IEEE transactions on medical imaging
Jan 2, 2024
Low-count positron emission tomography (PET) imaging is challenging because of the ill-posedness of this inverse problem. Previous studies have demonstrated that deep learning (DL) holds promise for achieving improved low-count PET image quality. How...
Deep learning approach using SPECT-to-PET translation for attenuation correction in CT-less myocardial perfusion SPECT imaging.
Annals of nuclear medicine
Dec 28, 2023
OBJECTIVE: Deep learning approaches have attracted attention for improving the scoring accuracy in computed tomography-less single photon emission computed tomography (SPECT). In this study, we proposed a novel deep learning approach referring to pos...
Early prediction of distant metastasis in patients with uterine cervical cancer treated with definitive chemoradiotherapy by deep learning using pretreatment [ 18 F]fluorodeoxyglucose positron emission tomography/computed tomography.
Nuclear medicine communications
Dec 27, 2023
OBJECTIVES: A deep learning (DL) model using image data from pretreatment [ 18 F]fluorodeoxyglucose ([ 18 F] FDG)-PET or computed tomography (CT) augmented with a novel imaging augmentation approach was developed for the early prediction of distant m...
Deep learning based synthesis of MRI, CT and PET: Review and analysis.
Medical image analysis
Dec 1, 2023
Medical image synthesis represents a critical area of research in clinical decision-making, aiming to overcome the challenges associated with acquiring multiple image modalities for an accurate clinical workflow. This approach proves beneficial in es...
Artificial Intelligence and Deep Learning for Advancing PET Image Reconstruction: State-of-the-Art and Future Directions.
Nuklearmedizin. Nuclear medicine
Nov 23, 2023
Positron emission tomography (PET) is vital for diagnosing diseases and monitoring treatments. Conventional image reconstruction (IR) techniques like filtered backprojection and iterative algorithms are powerful but face limitations. PET IR can be se...
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