Integrated segmentation and nonrigid registration for application in prostate image-guided radiotherapy

Authors:
Chao Lu;Sudhakar Chelikani;Zhe Chen;Xenophon Papademetris;Lawrence H. Staib;James S. Duncan
Affiliations:
Department of Electrical Engineering, Yale University, New Haven, CT;Department of Diagnostic Radiology, Yale University, New Haven, CT;Department of Diagnostic Radiology, Yale University, New Haven, CT;Department of Diagnostic Radiology, Yale University, New Haven, CT;Department of Electrical Engineering and Department of Diagnostic Radiology, Yale University, New Haven, CT;Department of Electrical Engineering and Department of Diagnostic Radiology, Yale University, New Haven, CT
Venue:
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part I
Year:
2010

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Abstract

Many current image-guided radiotherapy (IGRT) systems incorporate an in-room cone-beam CT (CBCT) with a radiotherapy linear accelerator for treatment day imaging. Segmentation of key anatomical structures (prostate and surrounding organs) in 3DCBCT images as well as registration between planning and treatment images are essential for determining many important treatment parameters. Due to the image quality of CBCT, previous work typically uses manual segmentation of the soft tissues and then registers the images based on the manual segmentation. In this paper, an integrated automatic segmentation/ constrained nonrigid registration is presented, which can achieve these two aims simultaneously. This method is tested using 24 sets of real patient data. Quantitative results show that the automatic segmentation produces results that have an accuracy comparable to manual segmentation, while the registration part significantly outperforms both rigid and non-rigid registration. Clinical application also shows promising results.