Latest AI and machine learning research in nuclear medicine for healthcare professionals.
PURPOSE: Whole-body positron emission tomography/computed tomography (PET/CT) has become a standard method of imaging patients with various disease conditions, especially cancer. Body-wide accurate quantification of disease burden in PET/CT images is important for characterizing lesions, staging disease, prognosticating patient outcome, planning treatment, and evaluating disease response to therap...
The analysis of positron emission tomography (PET) scan image is challenging due to a high level of noise and a low resolution and also because differences between healthy and demented are very subtle. High dimensional classification methods based on PET have been proposed to automatically discriminate between normal control group (NC) patients and patients with Alzheimer's disease (AD), with mild...
BACKGROUND: Few studies have shown the limitation of the World Health Organization (WHO)/ International Council for the Control of Iodine Deficiency (...
PURPOSE: Accurate tumor delineation in positron emission tomography (PET) images is crucial in oncology. Although recent methods achieved good results...
The aim of this study is to analyze the concordance between EDV, ESV and LVEF values derived from 18F-FDG PET, GSPECT and ECHO in patients with myocar...
OBJECTIVES: Post-treatment evaluations by CT/MRI (based on the International Working Group/Cotswolds meeting guidelines) and PET (based on Revised Res...