BACKGROUND: The comprehensiveness and maintenance of the American College of Radiology (ACR) Appropriateness Criteria (AC) makes it a unique resource for evidence-based clinical imaging decision support, but it is underutilized by clinicians. To faci...
Thermal cameras capture the infrared radiation emitted from a body in a contactless manner and can provide an indirect estimation of the autonomic nervous system (ANS) dynamics through the regulation of the skin temperature. This study investigates t...
Cell detection and tracking applied to in vivo fluorescence microscopy has become an essential tool in biomedicine to characterize 4D (3D space plus time) biological processes at the cellular level. Traditional approaches to cell motion analysis by m...
During the last two decades, as computer technology has matured and business scenarios have diversified, the scale of application of computer systems in various industries has continued to expand, resulting in a huge increase in industry data. As for...
Radiogenomics is a field where medical images and genomic profiles are jointly analyzed to answer critical clinical questions. Specifically, people want to identify non-invasive imaging biomarkers that are associated with both genomic features and cl...
Social and health care equity and justice should be prioritized by the mantra of medicine, first do no harm. Despite highly motivated national and global health strategies, there remains significant health care inequity. Intrinsic and extrinsic facto...
Medical imaging datasets usually exhibit domain shift due to the variations of scanner vendors, imaging protocols, etc. This raises the concern about the generalization capacity of machine learning models. Domain generalization (DG), which aims to le...
We hypothesize that artificial intelligence (AI) applied to relevant clinical testing in glaucoma has the potential to enhance the ability to detect glaucoma. This premise was discussed at the recent Collaborative Community on Ophthalmic Imaging meet...
Artificial intelligence (AI) is transforming the way we perform advanced imaging. From high-resolution image reconstruction to predicting functional response from clinically acquired data, AI is promising to revolutionize clinical evaluation of lung ...
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