Mariana Lazar, medical imaging researcher who investigates psychiatric disorders, talks about recent findings, mentoring students, and learning by doing.
Krzysztof Geras and Jan Witowski, machine learning researchers in medical imaging, talk about understanding one’s data, working across disciplines, and radiologists’ “new colleague.”
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.
Scientists combine particle physics and neuroscience to visualize a key element of the nervous system.
NYU 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.
Hong Hsi Lee, alumnus of the Biomedical Imaging & Technology PhD Program at NYU Grossman School of Medicine, has just completed postdoctoral training at our Center and is headed to a postdoctoral fellowship at Massachusetts General Hospital. We take a look at his journey.
An interest in machine learning in medicine sparked by a college project has taken Vatsal Sodha from Gujarat to Arizona to a bicoastal telecommute.
Scientists show that MRI signal can detect axonal features long assumed to be beyond the reach of magnetic resonance imaging.
Daniel Sodickson, vice chair for research at NYU Langone’s radiology department, talks about cultivating talent, finding “a room of one’s own,” and distrusting startup packages.