Nuclear Medicine

A deep learning approach to radiation dose estimation.

Currently methods for predicting absorbed dose after administering a radiopharmaceutical are rather ...

PET image super-resolution using generative adversarial networks.

The intrinsically low spatial resolution of positron emission tomography (PET) leads to image qualit...

A deep learning method for producing ventilation images from 4DCT: First comparison with technegas SPECT ventilation.

PURPOSE: The purpose of this study is to develop a deep learning (DL) method for producing four-dime...

Improvement of classification performance of Parkinson's disease using shape features for machine learning on dopamine transporter single photon emission computed tomography.

OBJECTIVE: To assess the classification performance between Parkinson's disease (PD) and normal cont...

Machine learning derived input-function in a dynamic F-FDG PET study of mice.

Tracer kinetic modelling, based on dynamic F-fluorodeoxyglucose (FDG) positron emission tomography (...

Projection Space Implementation of Deep Learning-Guided Low-Dose Brain PET Imaging Improves Performance over Implementation in Image Space.

Our purpose was to assess the performance of full-dose (FD) PET image synthesis in both image and si...

Deep learning-based interpretation of basal/acetazolamide brain perfusion SPECT leveraging unstructured reading reports.

PURPOSE: Basal/acetazolamide brain perfusion single-photon emission computed tomography (SPECT) has ...

A 3D deep convolutional neural network approach for the automated measurement of cerebellum tracer uptake in FDG PET-CT scans.

PURPOSE: The purpose of this work was to assess the potential of deep convolutional neural networks ...

Diagnostic Value of Lesion-specific Measurement of Myocardial Blood Flow Using Hybrid PET/CT.

BACKGROUND: We evaluated whether lesion-specific measurement of myocardial blood flow (MBF) and flow...

Correlation of cancer antigen 15-3 (CA15-3) serum level and bony metastases in breast cancer patients.

Cancer antigen 15-3 (CA15-3) is a common tumor marker and the serum level of this tumor marker is e...

Artificial intelligence for detecting small FDG-positive lung nodules in digital PET/CT: impact of image reconstructions on diagnostic performance.

OBJECTIVES: To evaluate the diagnostic performance of a deep learning algorithm for automated detect...

The clinical feasibility of deep learning-based classification of amyloid PET images in visually equivocal cases.

PURPOSE: Although most deep learning (DL) studies have reported excellent classification accuracy, t...

CNN-based PET sinogram repair to mitigate defective block detectors.

Positron emission tomography (PET) scanners continue to increase sensitivity and axial coverage by a...

Cognitive signature of brain FDG PET based on deep learning: domain transfer from Alzheimer's disease to Parkinson's disease.

PURPOSE: Although functional brain imaging has been used for the early and objective assessment of c...

Radiomics based on F-FDG PET/CT could differentiate breast carcinoma from breast lymphoma using machine-learning approach: A preliminary study.

PURPOSE: Our study assessed the ability F-fluorodeoxyglucose (FDG) positron emission tomography (PE...

Isolated Hepatic Metastasis of Prostate Cancer with Variable F-fluociclovine Uptake by PET/CT Imaging.

A 74-year-old man presented with rapid rising prostate-specific antigen (PSA) 2 years after treatmen...

MedGAN: Medical image translation using GANs.

Image-to-image translation is considered a new frontier in the field of medical image analysis, with...

Deep segmentation networks predict survival of non-small cell lung cancer.

Non-small-cell lung cancer (NSCLC) represents approximately 80-85% of lung cancer diagnoses and is t...

Partial-ring PET image restoration using a deep learning based method.

PET scanners with partial-ring geometry have been proposed for various imaging purposes. The incompl...

Predicting O-Water PET cerebral blood flow maps from multi-contrast MRI using a deep convolutional neural network with evaluation of training cohort bias.

To improve the quality of MRI-based cerebral blood flow (CBF) measurements, a deep convolutional neu...

Deep Learning in Quantitative PET Myocardial Perfusion Imaging: A Study on Cardiovascular Event Prediction.