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Deep learning helps categorize acute appendicitis on pelvic CT
A combined deep learning and radiomics model helps clinicians differentiate complicated from uncomplicated acute appendicitis on pelvic CT.
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Images in a 52-year-old woman with cardiac sarcoidosis. Standard-of-care imaging (top row) demonstrates a perfusion defect on SPECT images (top left) and corresponding FDG radiotracer uptake on PET/CT image (top right) at the interventricular septum (green arrows). On combined F-18 FDG-PET/MRI (bottom row), there is nodular late gadolinium enhancement (LGE) at the interventricular septum (orange arrows) with corresponding FDG uptake (blue arrows). Image courtesy of Radiology: Cardiothoracic Imaging.
Molecular Imaging
PET/MRI superior for diagnosing cardiac sarcoidosis
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IAEA's Rays of Hope initiative establishes anchor centers
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Appendix Blue 400
CT
Deep learning helps categorize acute appendicitis on pelvic CT
Molecular Imaging
PET/MRI superior for diagnosing cardiac sarcoidosis
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Just how effective is the use of synthetic mammography with DBT?
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Artificial Intelligence Ai Abstract 400
Nanox touts CT study using its AI software
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The new Magnetom Viato.Mobile MRI scanner. Image courtesy of Siemens Healthineers.
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