Nuclear Medicine

[The value of artificial and human intelligence - the example of bone scintigraphy].

We present a possible method of Artificial Intelligence (AI) based applications that can effectively filter noise-sensitive bone scintigraphy images. The use of special AI, based on preliminary examinations, allows us to significantly reduce study time or activity administered to the patient, thus reducing the patient, assistant, and physician radiation. We present the features of the AI filtering...

Ga-PSMA PET/CT versus CT and bone scan for investigation of PSA failure post radical prostatectomy.

OBJECTIVE: To evaluate the use of Gallium-68 prostate-specific membrane antigen positron emission tomography/computed tomography (Ga-PSMA PET/CT), compared with conventional CT abdomen/pelvis (CTAP) and whole body single photon emission CT bone scan (BS), for detection of local or distant metastasis following biochemical failure/recurrence in post-prostatectomy patients.

A deep learning approach to radiation dose estimation.

Currently methods for predicting absorbed dose after administering a radiopharmaceutical are rather crude in daily clinical practice. Most importantly...

PET image super-resolution using generative adversarial networks.

The intrinsically low spatial resolution of positron emission tomography (PET) leads to image quality degradation and inaccurate image-based quantitat...

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-dimensional computed tomography (4DCT) ventilation ima...

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 control (NC) when semi-quantitative indicators and sha...

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 (PET) is used to quantify glucose metabolism in hum...

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 sinogram space from low-dose (LD) PET images and sin...

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 been used to evaluate functional hemodynamics in p...

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 in automated measurement of cerebellum tracer upta...

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 reserve (MFR) by hybrid imaging of myocardial per...

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 evaluated during the treatment period (periodically...

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 detection of small F-FDG-avid pulmonary nodules in PET s...

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

Positron emission tomography (PET) scanners continue to increase sensitivity and axial coverage by adding an ever expanding array of block detectors. ...

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 cognitive dysfunction, there is a lack of generaliz...

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 (PET)/computed tomography (CT) radiomics to different...

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 treatment of prostate cancer with prostatectomy and salvag...

MedGAN: Medical image translation using GANs.

Image-to-image translation is considered a new frontier in the field of medical image analysis, with numerous potential applications. However, a large...

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 incomplete projection data obtained from this design caus...

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 the leading cause of cancer-related death worldwide...