Latest AI and machine learning research in nuclear medicine for healthcare professionals.
Groundnut oil is known as a good source of essential fatty acids which are significant in the physio...
RATIONALE AND OBJECTIVE: To compare the performance of large language model (LLM) based Gemini and G...
The current study aimed to predict lymphovascular invasion (LVI) using multiple machine learning alg...
BACKGROUND: Deep learning is the primary method for conducting automated analysis of SPECT bone scin...
PURPOSE: This study demonstrates the feasibility and benefits of using a deep learning-based approac...
BACKGROUND: Cardiovascular disease affects the carotid arteries, coronary arteries, aorta and the pe...
We propose strongly unrealistic data augmentation to improve the robustness of convolutional neural ...
Alzheimer disease (AD) exhibits spatially heterogeneous 3- or 4-repeat tau deposition across partici...
Target volumes for radiotherapy are usually contoured manually, which can be time-consuming and pron...
BACKGROUND: Stress myocardial perfusion single-photon emission computed tomography (SPECT) imaging (...
We aim to provide an overview of technical and clinical unmet needs in deep learning (DL) applicatio...
INTRODUCTION: We propose a novel approach for the non-invasive quantification of dynamic PET imaging...
Dynamic 2-[18F] fluoro-2-deoxy-D-glucose positron emission tomography (dFDG-PET) for human brain ima...
PURPOSE: Develop a universal lesion recognition algorithm for PET/CT and PET/MRI, validate it, and e...
This work proposes, for the first time, an image-based end-to-end self-normalization framework for p...
PURPOSE: Respiratory motion (RM) significantly impacts image quality in thoracoabdominal PET/CT imag...
Automatic tumor segmentation via positron emission tomography (PET) and computed tomography (CT) ima...
As the segment of diseased tissue in PET images is time-consuming, laborious and low accuracy, this ...
PURPOSE: Convolutional Neural Networks (CNNs) have emerged as transformative tools in the field of r...
Deep learning, particularly convolutional neural networks (CNNs), has advanced positron emission tom...
RATIONALE AND OBJECTIVES: This study investigated the use of deep learning-generated virtual positro...