Abstract
Segmentation remains the most time-consuming task in radiotherapy planning. In a fundamental paradigm shift, atlas segmentation recently emerged as a fully automated technology that relies on matching an image, through deformable registration, to a template with carefully segmented structures. The method works well for structures that do not have a clear border in low-contrast regions. Due to its practicability, the approach was recently incorporated by various vendors in their software solutions. With significant cost and time saving achievable through implementation of atlas segmentation in your clinic, the aim of this course is to familiarize you with the approach and terminology in a simple and intuitive presentation. Examples of integrating atlas segmentation in the daily clinical workflow will be presented to illustrate advantages and lessons learned when adapting this new technology in the clinic. Latest research findings in auto- segmenting difficult structures in thoracic and abdominal anatomy will also be presented. Learning objectives: 1. Understand how atlas-based segmentation simplifies segmentation for treatment planning 2. Show how atlas-based image segmentation can be integrated in the daily clinical workflow 3. Present current research findings and problems
Published Version
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