Nuclear Medicine

Machine learning-aided engineering of hydrolases for PET depolymerization.

Plastic waste poses an ecological challenge and enzymatic degradation offers one, potentially green ...

Evaluation Algorithm for the Effectiveness of Stroke Rehabilitation Treatment Using Cross-Modal Deep Learning.

It is important to study the evaluation algorithm for the stroke rehabilitation treatment effect to ...

Decentralized Distributed Multi-institutional PET Image Segmentation Using a Federated Deep Learning Framework.

PURPOSE: The generalizability and trustworthiness of deep learning (DL)-based algorithms depend on t...

Tc-PSMA targeted robot-assisted radioguided surgery during radical prostatectomy and extended lymph node dissection of prostate cancer patients.

OBJECTIVE: The feasibility of tracer production of technetium (Tc)-prostate-specific membrane antige...

Comparison of machine learning approaches for radioisotope identification using NaI(TI) gamma-ray spectrum.

This research aims at comparing the performance of different machine learning algorithms used for Na...

Contrast Media Reduction in Computed Tomography With Deep Learning Using a Generative Adversarial Network in an Experimental Animal Study.

OBJECTIVE: This feasibility study aimed to use optimized virtual contrast enhancement through genera...

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...

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 ...

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...

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

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

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...

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...