Krzysztof Geras and Jan Witowski, machine learning researchers in medical imaging, talk about understanding one’s data, working across disciplines, and radiologists’ “new colleague.”
Personalized, plain-language video reports can help patients better understand imaging test results, according to a new study led by radiologists at NYU Langone in collaboration with Visage Imaging and Siemens Healthineers.
Imaging researchers at NYU Langone Health are training AI models to recognize breast cancer in mammograms, with the potential to improve radiologists’ accuracy.
A computer program trained to see patterns among thousands of breast ultrasound images can aid physicians in accurately diagnosing breast cancer, a new study shows.
A combination of radiologists and AI reduced overdiagnosis and more accurately identified breast cancer in ultrasound exams.
Florian Knoll, incoming chair of imaging at University of Erlangen–Nuremberg, talks about his background, not being greedy, and why he does what he does.
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A New Way to Image Myelin
Scientists combine particle physics and neuroscience to visualize a key element of the nervous system.
Study finds MRI reduces the number of biopsies and detects more clinically significant cancers.
Trained to see patterns by analyzing thousands of chest X-rays, a computer program predicted with up to 80 percent accuracy which patients with COVID-19 would develop life-threatening complications within 4 days, a new study finds.
NYU Langone researchers won a deep learning challenge to detect lesions in digital breast tomosynthesis (DBT) images. We discuss the obstacles that DBT poses to deep learning and look at how our team navigated them.