The Department of Radiation Oncology and the Medical Physics Graduate Program jointly hosted the 2019 Samulski Lectureship to honor the legacy of Dr. Thaddeus V. Samulski. The topic of this year’s lectureship was “State-of-the Art of AI/Machine Learning in Medical Physics.” The lectures were delivered by Maryellen L. Giger, PhD, A.N. Pritzker Professor of Radiology at the University of Chicago and Joseph O. Deasy, PhD, the Chair of the Department of Medical Physics at the Memorial Sloan-Kettering Cancer Center. During the lecture, Dr. Giger discussed the history of Computer Aided Diagnosis (CAD) in detecting abnormalities in human breasts such as lesions and micro-calcifications, as well as the role of AI in improving the performance of CAD in the clinic. Speaking after Dr. Giger, Dr. Deasy presented about his work in applying different data-driven machine learning methods to explore topics in the Radiation Therapy field, including the correlation of Dose Volume Histogram profile for some organs-at-risk and the overall patient survival rate.
About Dr. Samulski:
Dr. Thaddeus V. Samulski (Thad) was recruited to Duke in 1986 to join the hyperthermia program under the leadership of Drs. James Oleson and Mark Dewhirst. Thad later assumed the leadership role of the Physics Division in the Department of Radiation Oncology. Among his many accomplishments while at Duke was the development of the magnetic resonance imaging for noninvasive temperature measurement in real time, in patients undergoing hyperthermia treatments. In addition to Thad’s many accomplishments, his research efforts in hyperthermia were recognized by his receipt of the J.Eugene Robinson Award for Excellence in Hyperthermia Research awarded to him in 1999 by the Society for Thermal Medicine.