Nuclear Medicine

Early diagnosis of Alzheimer's Disease: Graph theoretical analysis of cerebellar network features based on 18F-AV45 PET.

Pathological and neuroimaging changes in the cerebellum of Alzheimer's disease (AD) patients have been well documented. However, the changes in cerebellar amyloid plaque deposition connectivity networks during AD progression based on positron emission tomography (PET) imaging remain unclear. We selected 18F-florbetapir PET (18F-AV45 PET) imaging data from the Alzheimer's disease neuroimaging initi...

Enhancing uncertainty assessment in dynamic PET imaging with residual permutation and clustering.

Quantitative positron emission tomography (PET) is widely used for disease diagnosis and therapy monitoring, yet the reliability of kinetic parameters depends on robust uncertainty quantification. Existing Bayesian methods are computationally demanding, bootstrap approaches are noise-sensitive, and recent deep learning models often require large training datasets and lack physical scale sensitivit...

Deep learning cascade networks for segmentation of fluorine-18 sodium fluoride positron emission tomography scans of equine metacarpo- and metatarsophalangeal joints outperform atlas-based method.

OBJECTIVE: To create a labeled dataset and evaluate a convolutional neural network (CNN) for segmentation of fluorine-18 sodium fluoride PET scans of ...

Clinical validation of perfusion imaging with pulmonary function test data using Voronoi-based discretization.

Accurate lung function assessment is essential for diagnosing and managing diseases like COPD, pulmonary emboli, and lung cancer. Single-photon emissi...

Computational analysis of the Lengyel-Epstein system for the chlorite-iodide-malonic acid reaction using radial basis function neural network.

The chlorine dioxide-iodine-malonic acid (CDIMA) reaction governed by the Lengyel-Epstein equations is a canonical reaction-diffusion system known for...

Artificial intelligence for lung cancer: a systematic review of head‑to‑head CT, FDG PET/CT, and multimodal models across screening, staging, and prognosis.

BACKGROUND: Artificial intelligence (AI) has shown increasing potential in lung cancer imaging, particularly in detection, staging, prognosis, and rec...

Enhancing low-dose PET image recovery via edge perception and Mamba-guided network architecture.

Positron emission tomography (PET) is a sensitive molecular imaging technique used extensively in cancer diagnosis, neurology, and cardiovascular dise...

Single-Stage Lesion Identification in $^{68}$Ga-DOTATATE PET Images.

OBJECTIVE: Positron emission tomography (PET) is a commonly used imaging modality for assessment of neuroendocrine tumors (NETs), and lesion identific...

Precision imaging and evolving therapies in paragangliomas and pheochromocytomas: from molecular diagnostics to imaging-guided management.

Pheochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumors originating from neural crest-derived chromaffin tissue, marked by clinica...

Deep learning for synthetic PET imaging: a systematic mapping review of techniques, metrics, and clinical relevance.

BACKGROUND: Synthetic positron emission tomography (PET) imaging, enabled by deep learning, represents a promising approach to minimize radiation expo...

Spatial amyloid-informed multimodal brain age as an early marker of Alzheimer's-related vulnerability and risk stratification.

BACKGROUND: Brain age gap (BAG)-the difference between predicted and chronological age-captures neurobiological aging, but MRI-only models insufficien...

Assessment of iodine nutrition status in individual adults using machine learning: a cross-sectional study integrating multidimensional features.

Validation of a Deep-Learning Coregistration Framework for Long-Axial-Field-of-View PET/CT Using Low-Radiation-Exposure Protocols Across Various Tracers.

The advent of long-axial-field-of-view (LAFOV) PET/CT systems has significantly improved whole-body imaging by providing higher sensitivity and extend...

Quantification of PET activation in adipose tissue from non-contrast CT scans.

Brown adipose tissue (BAT) plays a key role in energy metabolism and cardiometabolic health. Its detection typically relies on 18F-FDG PET, which is c...

Beyond CT: Attenuation correction for stand-alone brain PET.

Accurate attenuation correction (AC) is essential for quantitative brain positron emission tomography (PET), but it presents a significant challenge f...

[Innovative imaging techniques for urothelial carcinoma].

BACKGROUND: Imaging guides the staging of urothelial carcinoma and thus plays a central role in treatment decisions. Current guidelines reflect the in...

Enhancing diagnostic safety with low iodine, low radiation CTPA classification using deep learning.

Pulmonary embolism (PE) is a life-threatening condition for which computed tomography pulmonary angiography (CTPA) is the standard diagnostic modality...

DBFANet: a dual-branch feature alignment network for automated detection of breast cancer bone metastasis.

Bone scan imaging for the detection of bone metastasis of breast cancer has been widely adopted; however, noise, anatomy superimposition, and small si...

State-of-the-art 32 cm field-of-view digital PET/CT system: preliminary study for protocols optimization and DRLs update.

The aim of this study was to assess the impact of a state-of-the-art 32 cm axial field-of-view GE Omni Legend PET/CT system on administered activity a...

Parametric imaging of dynamic long-axial-field-of-view PET scans: Technical challenges, statistical insights and clinical applications.

Dynamic long-axial-field-of-view (LAFOV) PET imaging offers unprecedented opportunities for quantitative assessment of tracer kinetics across the enti...