Nuclear Medicine

Heart and bladder detection and segmentation on FDG PET/CT by deep learning.

PURPOSE: Positron emission tomography (PET)/ computed tomography (CT) has been extensively used to q...

MR-assisted PET respiratory motion correction using deep-learning based short-scan motion fields.

PURPOSE: We evaluated the impact of PET respiratory motion correction (MoCo) in a phantom and patien...

The efficacy of F-FDG-PET-based radiomic and deep-learning features using a machine-learning approach to predict the pathological risk subtypes of thymic epithelial tumors.

OBJECTIVE: To examine whether the machine-learning approach using 18-fludeoxyglucose positron emissi...

"Virtual" attenuation correction: improving stress myocardial perfusion SPECT imaging using deep learning.

PURPOSE: Myocardial perfusion imaging (MPI) using single-photon emission computed tomography (SPECT)...

Deep learning-based image reconstruction and post-processing methods in positron emission tomography for low-dose imaging and resolution enhancement.

Image processing plays a crucial role in maximising diagnostic quality of positron emission tomograp...

Parametric image generation with the uEXPLORER total-body PET/CT system through deep learning.

PURPOSE: Total-body dynamic positron emission tomography/computed tomography (PET/CT) provides much ...

Fully automated deep learning powered calcium scoring in patients undergoing myocardial perfusion imaging.

BACKGROUND: To assess the accuracy of fully automated deep learning (DL) based coronary artery calci...

Deep learning-based attenuation correction for whole-body PET - a multi-tracer study with F-FDG,  Ga-DOTATATE, and F-Fluciclovine.

UNLABELLED: A novel deep learning (DL)-based attenuation correction (AC) framework was applied to cl...

Multi-task Deep Learning of Myocardial Blood Flow and Cardiovascular Risk Traits from PET Myocardial Perfusion Imaging.

BACKGROUND: Advanced cardiac imaging with positron emission tomography (PET) is a powerful tool for ...

Technical note: A PET/MR coil with an integrated, orbiting 511 keV transmission source for PET/MR imaging validated in an animal study.

BACKGROUND: MR-based methods for attenuation correction (AC) in PET/MRI either neglect attenuation o...

Radiation and iodine dose reduced thoraco-abdomino-pelvic dual-energy CT at 40 keV reconstructed with deep learning image reconstruction.

OBJECTIVE: To evaluate the feasibility of a simultaneous reduction of radiation and iodine doses in ...

Future of nuclear cardiology is bright: Promise of cardiac PET/CT and artificial intelligence.

Robot-Assisted Prostate-Specific Membrane Antigen-Radioguided Surgery in Primary Diagnosed Prostate Cancer.

The objective of this study was to evaluate the safety and feasibility of Tc-based prostate-specific...

Deep Learning-Based Diffusion-Weighted Magnetic Resonance Imaging in the Diagnosis of Ischemic Penumbra in Early Cerebral Infarction.

The prefiltered image was imported into the local higher-order singular value decomposition (HOSVD) ...

Cross-institutional outcome prediction for head and neck cancer patients using self-attention neural networks.

In radiation oncology, predicting patient risk stratification allows specialization of therapy inten...

Deep learning-based detection of parathyroid adenoma by Tc-MIBI scintigraphy in patients with primary hyperparathyroidism.

OBJECTIVE: It is important to detect parathyroid adenomas by parathyroid scintigraphy with 99m-techn...

A few-shot U-Net deep learning model for lung cancer lesion segmentation via PET/CT imaging.

Over the past few years, positron emission tomography/computed tomography (PET/CT) imaging for compu...

A back-projection-and-filtering-like (BPF-like) reconstruction method with the deep learning filtration from listmode data in TOF-PET.

PURPOSE: The time-of-flight (TOF) information improves signal-to-noise ratio (SNR) for positron emis...

Direct and indirect strategies of deep-learning-based attenuation correction for general purpose and dedicated cardiac SPECT.

PURPOSE: Deep-learning-based attenuation correction (AC) for SPECT includes both indirect and direct...

Deep learning-based tumour segmentation and total metabolic tumour volume prediction in the prognosis of diffuse large B-cell lymphoma patients in 3D FDG-PET images.

OBJECTIVES: To demonstrate the effectiveness of automatic segmentation of diffuse large B-cell lymph...

Artificial Intelligence in Head and Neck Imaging.

Artificial intelligence (AI) can be applied to head and neck imaging to augment image quality and va...