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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.
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PET/MRI superior for diagnosing cardiac sarcoidosis
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Appendix Blue 400
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Deep learning helps categorize acute appendicitis on pelvic CT
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Just how effective is the use of synthetic mammography with DBT?
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Deep learning helps categorize acute appendicitis on pelvic CT
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Appendix Blue 400
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.
Nanox touts CT study using its AI software
Sirona inks deals with AI developers
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