title: Deformable image registration with inclusion of autodetected homologous tissue features.
abstract: A novel deformable registration algorithm is proposed in the application of radiation therapy. The algorithm starts with autodetection of a number of points with distinct tissue features. The feature points are then matched by using the scale invariance features transform (SIFT) method. The associated feature point pairs are served as landmarks for the subsequent thin plate spline (TPS) interpolation. Several registration experiments using both digital phantom and clinical data demonstrate the accuracy and efficiency of the method. For the 3D phantom case, markers with error less than 2 mm are over 85% of total test markers, and it takes only 2-3 minutes for 3D feature points association. The proposed method provides a clinically practical solution and should be valuable for various image-guided radiation therapy (IGRT) applications.
authors.affiliation: Key Laboratory for Health Informatics, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
authors.forename: Qingsong
authors.initials: Q
authors.lastname: Zhu
authors.forename: Jia
authors.initials: J
authors.lastname: Gu
authors.forename: Yaoqin
authors.initials: Y
authors.lastname: Xie
mesh_terms: D000465:Algorithms; D056973:Four-Dimensional Computed Tomography / Q000379:methods; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods; D019047:Phantoms, Imaging; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012984:Software; D013382:Subtraction Technique; D013997:Time Factors; D060726:Torso / Q000000981:diagnostic imaging*