Destroying cancers with radiation has a long history dating back to 1896. Before computers and more importantly CT scanners became widely available, the early radiotherapy treatments were planned and calculated using pencil, paper and coordinate grids drawn directly on patients body. Today, radiotherapy planning is a much easier process that is done completely electronically and without any manual calculations. Computer‐aided radiotherapy treatment planning opened up a huge research field on its own. In this seminar, we will introduce the audience to the research problems in automated treatment planning, many of which overlap with the familiar discrete signal and image processing fields, as well as image reconstruction and discrete optimization. Unlike in most other fields, just slightly improved or more efficient solutions in radiotherapy planning lead to improved patient outcomes, including better survival rates and reduced side effects.
Yevgen is a Software Architect at RefleXion Medical responsible for engineering RefleXion’s treatment planning system, and dose delivery algorithms. Prior to RefleXion, Yevgen served as a Research Scientist at Accuray, where he focused on sub‐millimeter accuracy in dose calculation, automation of large scale Monte‐Carlo simulations, and treatment planning beam optimization. Earlier in his career, Yevgen in collaboration with CMU researchers co‐founded SpiralGen, a company specializing in compiler automation tools for performance critical signal processing applications. Yevgen holds a BS in Computer Science from Drexel University and a PhD in Electrical and Computer Engineering from Carnegie Mellon.