title: Evaluation of various deformable image registration algorithms for thoracic images.
abstract: We evaluated the accuracy of one commercially available and three publicly available deformable image registration (DIR) algorithms for thoracic four-dimensional (4D) computed tomography (CT) images. Five patients with esophagus cancer were studied. Datasets of the five patients were provided by DIR-lab (dir-lab.com) and consisted of thoracic 4D CT images and a coordinate list of anatomical landmarks that had been manually identified. Expert landmark correspondence was used for evaluating DIR spatial accuracy. First, the manually measured displacement vector field (mDVF) was obtained from the coordinate list of anatomical landmarks. Then the automatically calculated displacement vector field (aDVF) was calculated by using the following four DIR algorithms: B-spine implemented in Velocity AI (Velocity Medical, Atlanta, GA, USA), free-form deformation (FFD), Horn-Schunk optical flow (OF) and Demons in DIRART of MATLAB software. Registration error is defined as the difference between mDVF and aDVF. The mean 3D registration errors were 2.7 ± 0.8 mm for B-spline, 3.6 ± 1.0 mm for FFD, 2.4 ± 0.9 mm for OF and 2.4 ± 1.2 mm for Demons. The results showed that reasonable accuracy was achieved in B-spline, OF and Demons, and that these algorithms have the potential to be used for 4D dose calculation, automatic image segmentation and 4D CT ventilation imaging in patients with thoracic cancer. However, for all algorithms, the accuracy might be improved by using the optimized parameter setting. Furthermore, for B-spline in Velocity AI, the 3D registration error was small with displacements of less than ∼10 mm, indicating that this software may be useful in this range of displacements.
authors.affiliation: Department of Radiation Oncology, Tohoku University School of Medicine, 1-1 Seiryo-machi, Aoba-ku, Sendai 980-8574, Japan.
authors.forename: Noriyuki
authors.initials: N
authors.lastname: Kadoya
authors.forename: Yukio
authors.initials: Y
authors.lastname: Fujita
authors.forename: Yoshiyuki
authors.initials: Y
authors.lastname: Katsuta
authors.forename: Suguru
authors.initials: S
authors.lastname: Dobashi
authors.forename: Ken
authors.initials: K
authors.lastname: Takeda
authors.forename: Kazuma
authors.initials: K
authors.lastname: Kishi
authors.forename: Masaki
authors.initials: M
authors.lastname: Kubozono
authors.forename: Rei
authors.initials: R
authors.lastname: Umezawa
authors.forename: Toshiyuki
authors.initials: T
authors.lastname: Sugawara
authors.forename: Haruo
authors.initials: H
authors.lastname: Matsushita
authors.forename: Keiichi
authors.initials: K
authors.lastname: Jingu
mesh_terms: D000465:Algorithms; D004938:Esophageal Neoplasms / Q000000981:diagnostic imaging* / Q000532:radiotherapy; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D013902:Radiography, Thoracic / Q000379:methods*; D061089:Radiotherapy, Image-Guided / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012984:Software; D013382:Subtraction Technique; D014057:Tomography, X-Ray Computed / Q000379:methods*
keywords: adaptive radiotherapy; deformable image registration; image fusion; radiotherapy