Automation is changing the way we perform clinical tasks, creating more efficient, more consistent, and safer workflows. The aim of this webinar is to educate clinicians on automation and deep learning as it applies to auto segmentation to improve the treatment planning workflow. Radformation’s Chief Science Officer, Alan Nelson, DMP, DABR, will outline the technology that allows for fast, reliable contours. Over the course of the webinar we will detail:
- The concepts involved in training a Convolutional Neural Network with a U-Net architecture.
- How to approach optimizing the data pipeline for training neural networks and why it is important.
- How a deep learning algorithm can fit into the clinical workflow in a way that maximizes safety and efficiency.
This webinar is intended for radiation therapy physicists, dosimetrists, and administrators interested in learning about the technology that enables fast, AI-driven contouring.
We’ve applied for 1.0 CAMPEP and MDCB credits for this webinar.