PURPOSE: The aim of this study is to develop a deep neural network to diagnosis Alzheimer's disease and categorize the stages of the disease using FDG-PET scans. Fluorodeoxyglucose positron emission tomography (FDG-PET) is a highly effective diagnost...
This review article focuses on PET detector technology, which is the most crucial factor in determining PET image quality. The article highlights the desired properties of PET detectors, including high detection efficiency, spatial resolution, energy...
Dynamic PET imaging provides superior physiological information than conventional static PET imaging. However, the dynamic information is gained at the cost of a long scanning protocol; this limits the clinical application of dynamic PET imaging. We ...
European journal of nuclear medicine and molecular imaging
Sep 22, 2023
PURPOSE: Alzheimer's disease (AD) is a heterogeneous disease that presents a broad spectrum of clinicopathologic profiles. To date, objective subtyping of AD independent of disease progression using brain imaging has been required. Our study aimed to...
The effectiveness and precision of disease diagnosis and treatment have increased, thanks to developments in clinical imaging over the past few decades. Science is developing and progressing steadily in imaging modalities, and effective outcomes are ...
European journal of nuclear medicine and molecular imaging
Sep 6, 2023
PURPOSE: The axial field of view (AFOV) of a positron emission tomography (PET) scanner greatly affects the quality of PET images. Although a total-body PET scanner (uEXPLORER) with a large AFOV is more sensitive, it is more expensive and difficult t...
Image reconstruction for positron emission tomography (PET) has been developed over many decades, with advances coming from improved modelling of the data statistics and improved modelling of the imaging physics. However, high noise and limited spati...
OBJECTIVE: Normal interictal [ F]FDG-PET can be predicted from the corresponding T1w MRI with Generative Adversarial Networks (GANs). A technique we call SIPCOM (Subtraction Interictal PET Co-registered to MRI) can then be used to compare epilepsy pa...
Deep learning (DL)-based denoising of low-dose positron emission tomography (LDPET) and low-dose computed tomography (LDCT) has been widely explored. However, previous methods have focused only on single modality denoising, neglecting the possibility...
European journal of nuclear medicine and molecular imaging
Aug 22, 2023
OBJECTIVE: To develop and independently externally validate robust prognostic imaging biomarkers distilled from PET images using deep learning techniques for precise survival prediction in patients with diffuse large B cell lymphoma (DLBCL).
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