معرفی
Michael F. McNitt-Gray is a Professor in Radiological Sciences at the University of California, Los Angeles (UCLA). His research focuses on medical imaging technologies, particularly in computed tomography (CT), radiation dose assessment, and artificial intelligence applications in medical imaging. He holds a PhD in Biomedical Physics from UCLA (1993), an MSEE from Carnegie-Mellon University (1980), and a BSEE from Washington University in St. Louis (1979).
Key areas of research include optimizing CT protocols, radiation dose reduction, quantitative imaging biomarkers, and lung disease diagnosis. He has contributed to initiatives like the Lung Image Database Consortium (LIDC) and developed tools for radiomic feature standardization and AI-driven image analysis. His work addresses challenges in lung cancer screening, nodule detection, and emphysema assessment, with a strong emphasis on reproducibility and clinical translation.
His awards include Fellowships from the American Association of Physicists in Medicine (2011) and the American College of Radiology (2017). His publications span over three decades, addressing topics such as CT dose estimation, AI in medical imaging, and radiomics. He has collaborated extensively on multi-institutional studies and clinical trials, focusing on improving diagnostic accuracy and safety in medical imaging.
