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Positron-Emission Tomography

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Recovery of the spatially-variant deformations in dual-panel PET reconstructions using deep-learning.

Physics in medicine and biology
Dual panel PET systems, such as Breast-PET (B-PET) scanner, exhibit strong asymmetric and anisotropic spatially-variant deformations in the reconstructed images due to the limited-angle data and strong depth of interaction effects for the oblique LOR...

Greater accuracy of radiomics compared to deep learning to discriminate normal subjects from patients with dementia: a whole brain 18FDG PET analysis.

Nuclear medicine communications
METHODS: 18F-FDG brain PET and clinical score were collected in 85 patients with dementia and 125 healthy controls (HC). Patients were assigned to various form of dementia on the basis of clinical evaluation, follow-up and voxels comparison with HC u...

Artificial intelligence in immunotherapy PET/SPECT imaging.

European radiology
OBJECTIVE: Immunotherapy has dramatically altered the therapeutic landscape for oncology, but more research is needed to identify patients who are likely to achieve durable clinical benefit and those who may develop unacceptable side effects. We inve...

Attenuation correction and truncation completion for breast PET/MR imaging using deep learning.

Physics in medicine and biology
. Simultaneous PET/MR scanners combine the high sensitivity of MR imaging with the functional imaging of PET. However, attenuation correction of breast PET/MR imaging is technically challenging. The purpose of this study is to establish a robust atte...

Empowering PET: harnessing deep learning for improved clinical insight.

European radiology experimental
This review aims to take a journey into the transformative impact of artificial intelligence (AI) on positron emission tomography (PET) imaging. To this scope, a broad overview of AI applications in the field of nuclear medicine and a thorough explor...

Quasi-supervised learning for super-resolution PET.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Low resolution of positron emission tomography (PET) limits its diagnostic performance. Deep learning has been successfully applied to achieve super-resolution PET. However, commonly used supervised learning methods in this context require many pairs...

Deep learning-based PET image denoising and reconstruction: a review.

Radiological physics and technology
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
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)
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
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...