SU-E-J-92: CERR: New Tools to Analyze Image Registration Precision

Area of Science:

• Radiotherapy research
• Medical image analysis
• Computational environments

Background:

• The Computational Environment for Radiotherapy Research (CERR) is a widely cited platform for radiotherapy research.
• Image registration is crucial for many radiotherapy research studies, including outcomes modeling and algorithm prototyping.

Purpose of the Study:

• To introduce new software tools and updates within CERR.
• To enhance the analysis of image registration accuracy and other research functionalities.

Main Methods:

• CERR has been integrated with image registration frameworks (Plastimatch, ITK).
• New analysis tools include Distance Discordance Histograms (DDH) and MirrorScope for evaluating registration accuracy.
• Programmatic feature extraction and interfacing with statistical software (SPSS, Matlab) were implemented.

Main Results:

• MirrorScope visually identifies accurate registrations through symmetric patterns.
• Asymmetrical patterns in MirrorScope indicate regions of registration imperfection.

Conclusions:

• CERR updates enhance its utility for radiotherapy research.
• MirrorScope provides an intuitive and effective method for monitoring image registration accuracy, surpassing traditional visual methods.