Latest AI and machine learning research in nuclear medicine for healthcare professionals.
Accelerated Single Photon Emission Computed Tomography (SPECT) imaging, achieved by reducing either the number of projection angles or the acquisition time per angle, enhances clinical workflow efficiency but introduces elevated noise. Although deep learning-based methods promises to overcome this limitation, their practical application is hindered by the reliance on large datasets makes deve...
Foundation models (FMs), large neural networks pretrained on extensive and diverse datasets, have revolutionized artificial intelligence and demonstrated significant promise in medical imaging by enabling robust performance with limited labeled data. Although numerous surveys have reviewed the application of FMs in healthcare, brain imaging remains underrepresented, despite its critical role in th...
BACKGROUND: Cervical squamous cell carcinoma is a major global health burden, with many patients presenting with locally advanced disease requiring co...
PURPOSE: Preoperative identification of lymph node metastasis (LNM) in cervical cancer is crucial for guiding therapeutic strategies but remains clini...
Accurate non-invasive identification of hydroxyapatite (HA) deposits is important for diagnosing calcific musculoskeletal disease and quantifying vasc...
Polymyalgia rheumatica (PMR) is a common immune-mediated inflammatory disease affecting older adults over 50 years of age and is characterized by cons...
BACKGROUND: Hybrid single-photon emission computed tomography (SPECT)/computed tomography (CT) is used for the differential diagnosis of thyrotoxicosi...
Carotid atherosclerosis is a major cause of ischemic stroke, historically managed according to luminal stenosis severity. However, stenosis alone fail...
PURPOSE: This study aimed to develop and validate a non-invasive, multimodal radiomics model based on preoperative 1⁸F-FDG PET/CT to predict CLDN18.2 ...
BACKGROUND: Virtual monoenergetic imaging (VMI) at 40 keV improves iodine attenuation in colon cancer CT but is constrained by severe image noise. Dee...
Multi-Scan Total-Body PET/CT imaging, including dual-time-point and multi-tracer protocols, provides valuable metabolic information for enhanced disea...
BACKGROUND: Sentinel lymph node biopsy (SLNB) is the standard for staging melanoma. Traditional dual-mapping with technetium-99m radioisotope (RI) and...
The distribution of produced isotopes during proton therapy can be imaged with Positron Emission Tomography (PET) to verify dose delivery. However, bi...
Pulmonary sarcoidosis is a heterogeneous granulomatous disease with an unpredictable clinical course, in which accurate assessment of disease activity...
OBJECTIVES: To investigate the value of machine learning classifiers incorporating dual-layer spectral CT (DLCT) parameters for preoperative predictio...
INTRODUCTION: Lung cancer is the leading cause of cancer-related deaths worldwide, emphasizing the need for early and accurate diagnosis. Precise segm...
Polyethylene terephthalate (PET) hydrolases efficiently hydrolyze the ester bonds in PET, converting it into valuable monomers or oligomers, offering ...
OBJECTIVES: Accurate noninvasive classification of hepatic lesions remains a diagnostic challenge, particularly on conventional CT. Photon Counting De...
Developing diagnostic biomarkers for Alzheimer's disease (AD) is at the cutting edge of interdisciplinary research and technical advancement. This com...
The phase 2 LUNAR trial randomized (1:1) patients with oligorecurrent hormone-sensitive prostate cancer to neoadjuvant [177Lu]Lu-PSMA-I&T (2 cycles, 6...