Latest AI and machine learning research in nuclear medicine for healthcare professionals.
The rapid advancements in PET technology, coupled with the need for accurate and efficient imaging, necessitate the development of robust and generalizable methods for CT-free attenuation and scatter correction (ASC). Deep learning offers a promising solution, but exhibits limited performance when tested in diverse clinical settings and varying imaging conditions. We propose a few-shot fine-tuning...
OBJECTIVES: To develop and validate a deep learning-based model capable of generating dopamine transporter (DAT) images from early-phase [18F]-FP-CIT positron emission tomography (PET) imaging. MATERIALS AND METHODS: Conditional generative adversarial network was trained using 477 dual-phase [¹⁸F]-FP-CIT PET scans acquired with a conventional PET system. The model generated delayed-phase images fr...
BACKGROUND: To improve screening for cardiac amyloidosis (CA), several models using artificial intelligence (AI) and conventional statistics have been...
PURPOSE OF REVIEW: Myocarditis presents with heterogenous clinical manifestations and remains diagnostically challenging due to nonspecific biomarkers...
The early diagnosis of Parkinson's disease (PD) using SPECT imaging continues to be challenging due to the subtle dopaminergic deficits present in the...
BACKGROUND: Breast cancer is the most frequently diagnosed cancer among women. Accurate diagnosis and effective management rely heavily on high-qualit...
The century-old vision of a "magic bullet" in oncology is being realized through the paradigm of precision theranostics, which formally integrates tar...
OBJECTIVE: In positron emission tomography (PET)/magnetic resonance imaging (MRI), attenuation correction (AC) for PET of the head is achieved by MRI ...
INTRODUCTION: Hashimoto's thyroiditis is the leading cause of hypothyroidism in iodine-sufficient regions and is often accompanied by various comorbid...
BACKGROUND: The aim of this novel study was to explore the possibility of the development of a machine learning (ML) model that can predict early resp...
BACKGROUND: Automatic segmentation of gliomas on amino acid PET is essential for quantitative tumor assessment, a pillar in monitoring gliomas under t...
Positron emission tomography (PET) has been used in pediatric oncology since the modality gained traction 20 years ago but has been used more sparingl...
Small cell lung cancer (SCLC) is an aggressive pulmonary neuroendocrine carcinoma characterized by rapid progression and early metastasis. Despite rec...
OBJECTIVE: To evaluate the feasibility of cerebral computed tomography angiography (CTA) obtained with reduced iodine and low radiation at 70 kVp and ...
Ewing sarcoma is a highly aggressive small round cell sarcoma primarily affecting children and adolescents. Imaging plays a central role from diagnosi...
OBJECTIVE: Microsatellite instability (MSI) has emerged as a key predictive biomarker for chemotherapy and immunotherapy response, and as a prognostic...
BACKGROUND: Accurate pretreatment assessment of the extent of tumor invasion and status of cervical lymph node metastasis is essential for staging and...
90Y-labeled microsphere (90Y-microsphere) hepatic arterial radioembolization is a direct treatment for hepatic neoplasms. Before therapy, the fraction...
Long axial field-of-view (AFOV) PET-CT instruments have significantly higher sensitivity than conventional PET scanners allowing for reduced scan time...
CONTEXT: Incidental thyroid findings (ITFs) are increasingly detected on imaging performed for non-thyroid indications. Their prevalence, features, an...