Nuclear Medicine

AI-Based Detection, Classification and Prediction/Prognosis in Medical Imaging:: Towards Radiophenomics.

Artificial intelligence (AI) techniques have significant potential to enable effective, robust, and ...

Clinical Applications of Artificial Intelligence in Positron Emission Tomography of Lung Cancer.

The ability of a computer to perform tasks normally requiring human intelligence or artificial intel...

Artificial Intelligence and Cardiac PET/Computed Tomography Imaging.

Artificial intelligence is an important technology, with rapidly expanding applications for cardiac ...

Artificial Intelligence in Vascular-PET:: Translational and Clinical Applications.

Positron emission tomography (PET) offers an incredible wealth of diverse research applications in v...

[[SPECT] 5. Application of Artificial Intelligence in Nuclear Medicine for SPECT].

Self-normalized Classification of Parkinson's Disease DaTscan Images.

Classifying SPECT images requires a preprocessing step which normalizes the images using a normaliza...

Fully Automated Gross Tumor Volume Delineation From PET in Head and Neck Cancer Using Deep Learning Algorithms.

PURPOSE: The availability of automated, accurate, and robust gross tumor volume (GTV) segmentation a...

Deep learning based timing calibration for PET.

Neural network has been found an increasingly wide utilization in all fields. Owing to the fact that...

Deep Learning for Predicting Gamma-Ray Interaction Positions in LYSO Detector.

Positron Emission Tomography (PET) is among the most commonly used medical imaging modalities in cli...

Development of a deep learning method for CT-free correction for an ultra-long axial field of view PET scanner.

INTRODUCTION: The possibility of low-dose positron emission tomography (PET) imaging using high sens...

Analysis of Human Head Motion and Robotic Compensation for PET Imaging Studies.

Functional medical imaging systems can provide insights into brain activity during various tasks, bu...

IMPROVEMENTS OF 111IN SPECT IMAGES RECONSTRUCTED WITH SPARSELY ACQUIRED PROJECTIONS BY DEEP LEARNING GENERATED SYNTHETIC PROJECTIONS.

The aim was to improve single-photon emission computed tomography (SPECT) quality for sparsely acqui...

ACTIVITY CONCENTRATION ESTIMATION IN AUTOMATED KIDNEY SEGMENTATION BASED ON CONVOLUTION NEURAL NETWORK METHOD FOR 177LU-SPECT/CT KIDNEY DOSIMETRY.

For 177Lu-DOTATATE treatments, dosimetry based on manual kidney segmentation from computed tomograph...

Potential Applications of Artificial Intelligence and Machine Learning in Radiochemistry and Radiochemical Engineering.

Artificial intelligence and machine learning are poised to disrupt PET imaging from bench to clinic....

The Evolution of Image Reconstruction in PET: From Filtered Back-Projection to Artificial Intelligence.

PET can provide functional images revealing physiologic processes in vivo. Although PET has many app...

Artificial Intelligence-Based Image Enhancement in PET Imaging: Noise Reduction and Resolution Enhancement.

High noise and low spatial resolution are two key confounding factors that limit the qualitative and...

Toward High-Throughput Artificial Intelligence-Based Segmentation in Oncological PET Imaging.

Artificial intelligence (AI) techniques for image-based segmentation have garnered much attention in...

Computational methods for the prediction of chromatin interaction and organization using sequence and epigenomic profiles.

The exploration of three-dimensional chromatin interaction and organization provides insight into me...

Feasibility of Deep Learning-Guided Attenuation and Scatter Correction of Whole-Body 68Ga-PSMA PET Studies in the Image Domain.

OBJECTIVE: This study evaluates the feasibility of direct scatter and attenuation correction of whol...

Automated classification of increased uptake regions in bone single-photon emission computed tomography/computed tomography images using three-dimensional deep convolutional neural network.

OBJECTIVE: This study proposes an automated classification of benign and malignant in highly integra...

Performance Evaluation of a Deep Learning System for Differential Diagnosis of Lung Cancer With Conventional CT and FDG PET/CT Using Transfer Learning and Metadata.

PURPOSE: We aimed to evaluate the performance of a deep learning system for differential diagnosis o...