AIMC Topic: Positron-Emission Tomography
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The use of weather nowcasting convolutional neural network extrapolators in cardiac PET imaging.
Journal of medical radiation sciences
Jun 28, 2023
INTRODUCTION: Algorithms to predict short-term changes in local weather modalities have been used in meteorology for many years. These algorithms predict the temporospatial change in the movement of weather patterns such as cloud cover or precipitati...
Deep learning model for automatic image quality assessment in PET.
BMC medical imaging
Jun 5, 2023
BACKGROUND: A variety of external factors might seriously degrade PET image quality and lead to inconsistent results. The aim of this study is to explore a potential PET image quality assessment (QA) method with deep learning (DL).
A Two-Branch Neural Network for Short-Axis PET Image Quality Enhancement.
IEEE journal of biomedical and health informatics
Jun 5, 2023
The axial field of view (FOV) is a key factor that affects the quality of PET images. Due to hardware FOV restrictions, conventional short-axis PET scanners with FOVs of 20 to 35 cm can acquire only low-quality PET (LQ-PET) images in fast scanning ti...
Imaging of lung cancer.
Current problems in cancer
Jun 4, 2023
Lung cancer is the leading cause of cancer-related mortality globally. Imaging is essential in the screening, diagnosis, staging, response assessment, and surveillance of patients with lung cancer. Subtypes of lung cancer can have distinguishing imag...
Predicting FDG-PET Images From Multi-Contrast MRI Using Deep Learning in Patients With Brain Neoplasms.
Journal of magnetic resonance imaging : JMRI
Jun 1, 2023
BACKGROUND: F-fluorodeoxyglucose (FDG) positron emission tomography (PET) is valuable for determining presence of viable tumor, but is limited by geographical restrictions, radiation exposure, and high cost.
Inter-crystal scattering event identification using a novel silicon photomultiplier signal multiplexing method.
Physics in medicine and biology
May 22, 2023
Identifying the inter-crystal scatter (ICS) events and recovering the first interaction position enables the accurate determination of the line-of-response in positron emission tomography (PET). However, conventional silicon photomultiplier (SiPM) si...
Deep learning application for the classification of Alzheimer's disease using F-flortaucipir (AV-1451) tau positron emission tomography.
Scientific reports
May 19, 2023
The positron emission tomography (PET) with F-flortaucipir can distinguish individuals with mild cognitive impairment (MCI) and Alzheimer's disease (AD) from cognitively unimpaired (CU) individuals. This study aimed to evaluate the utility of F-flort...
Deep learning-based PET/MR radiomics for the classification of annualized relapse rate in multiple sclerosis.
Multiple sclerosis and related disorders
May 9, 2023
Background Annualized Relapse Rate (ARR) is one of the most important indicators of disease progression in patients with Multiple Sclerosis (MS). However, imaging markers that can effectively predict ARR are currently unavailable. In this study, we d...
18F-FDG PET/CT Image Deep Learning Predicts Colon Cancer Survival.
Contrast media & molecular imaging
May 4, 2023
Colon cancer is a type of cancer that begins in the large intestine. In the process of efficacy evaluation, postoperative recurrence prediction and metastasis monitoring of colon cancer, traditional medical image analysis methods are highly dependent...
Clinical application of AI-based PET images in oncological patients.
Seminars in cancer biology
Mar 10, 2023
Based on the advantages of revealing the functional status and molecular expression of tumor cells, positron emission tomography (PET) imaging has been performed in numerous types of malignant diseases for diagnosis and monitoring. However, insuffici...
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