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AI-driven Images in Radiation Therapy
Challenges for Usability & User Experience
Feb. 6, 2019

David J Gilmore, PhD, Elekta

New products for treating cancer with radiation therapy can provide therapists with high quality MR images in real-time, which can enable them to detect patient and tumor movements. This, in turn, creates the potential for much more precise and effective treatments for cancer.However, this creates tasks for the therapist that they are not used to (monitoring MR images for movement of the tumor or of critical organs).

Ensuring that the new, better technology is as safe and effective as the old technologies is the first challenge. The second challenge is deploying artificial intelligence – in the form of image processing – to detect these movements both automatically and much more precisely, whilst not interfering with the therapists ability to do their job. It seems obvious that the end result should be better for the user and for the patient, but demonstrating this and delivering on usability and user experience is non-trivial.

About the Speaker

David GilmoreDavid has over 30 years experience studying usability and user experience at the intersection of hardware and software, with 20+ experience using this expertise to develop real products. As well as Elekta’s Unity MR-Linac (discussed in this presentation) David was also the user experience lead for Logitech / Ultimate Ear’s Boom range of bluetooth speakers, and for GE Power’s ActivePoint HMI system for gas-fired power plants. Further back in time he also worked at Intel, IDEO and Apple, as well as teaching human factors and HCI at the University of Nottingham.

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