PURPOSE: The aim of this study is to convert low-dose PET (L-PET) images to full-dose PET (F-PET) images based on our Diffused Multi-scale Generative Adversarial Network (DMGAN) to offer a potential balance between reducing radiation exposure and mai...
PURPOSE: Commonly used MR image quality (IQ) metrics have poor concordance with radiologist-perceived diagnostic IQ. Here, we develop and explore deep feature distances (DFDs)-distances computed in a lower-dimensional feature space encoded by a convo...
Alzheimer's disease (AD) is a type of brain disorder that is becoming more prevalent worldwide. It is a progressive and irreversible condition that gradually impairs memory and cognitive abilities, eventually making it difficult to perform even basic...
Cortical parcellation delineates the cerebral cortex into distinct regions according to their distinctiveness in anatomy and/or function, which is a fundamental preprocess in brain cortex analysis and can influence the accuracy and specificity of sub...
Collecting annotations from multiple independent sources could mitigate the impact of potential noises and biases from a single source, which is a common practice in medical image segmentation. However, learning segmentation networks from multi-sourc...
Tuberculosis is a high-mortality infectious disease. Manual sputum smear microscopy is a common and effective method for screening tuberculosis. However, it is time-consuming, labor-intensive, and has low sensitivity. In this study, we propose ResGlo...
Cancer is a global health concern because of a significant mortality rate and a wide range of affected organs. Early detection and accurate classification of cancer types are crucial for effective treatment. Imaging tests on different image modalitie...
Timelapse microscopy has recently been employed to study the metabolism and physiology of cyanobacteria at the single-cell level. However, the identification of individual cells in brightfield images remains a significant challenge. Traditional inten...
Complete and high-quality photodocumentation in esophagoduodenogastroscopy (EGD) is essential for accurately diagnosing upper gastrointestinal diseases by reducing blind spot rates. Automated Photodocumentation Task (APT), an artificial intelligence-...
OBJECTIVES: Deep learning reconstruction of magnetic resonance imaging (MRI) allows to either improve image quality of accelerated sequences or to generate high-resolution data. We evaluated the interaction of conventional acceleration and Deep Resol...
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