WE-E-213CD-10: A Robust 2D/3D Image Registration System for Pediatric Patient Setup in External Beam Radiotherapy

Medical Physics
Jian WuZuofeng Li

Abstract

To develop a neural network based registration quality evaluator (RQE) that can improve the 2D/3D image registration robustness for pediatric patient setup in external beam radiotherapy. X-ray setup images of six pediatric patients with brain tumors received proton therapies were retrospectively registered with their treatment planning computed tomography (CT) images. A neural network based pattern classifier was used as an RQE to classify 2D/3D rigid registration solutions as successful or unsuccessful based on features of the similarity value surfaces near the point-of-solution. The supervised training and test datasets were generated by rigidly registering a pair of orthogonal daily setup x-ray images to the treatment planning CTs. The best solution for each registration task was selected from 50 optimizing attempts that differed only by the initial transformation parameters. The distance from each individual solution to the best solution in the normalized parametrical space was compared to a user- defined error threshold to determine whether that solution was successful. The supervised training was then used to train the RQE. The performance of the RQE was evaluated using the test dataset that consisted of registration resu...Continue Reading

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