title: Validation of three deformable image registration algorithms for the thorax.
abstract: Deformable image registration (DIR) has been proposed for lung ventilation calculation using 4D CT. Spatial accuracy of DIR can be evaluated using expert landmark correspondences. Additionally, image differences between the deformed and the target images give a degree of accuracy of DIR algorithms for the same image modality registration. DIR of the normal end-expiration (50%), end-inspiration (0%), midexpiration (30%), and midinspiration image (70%) phases of the 4D CT images was used to correlate the voxels between the respiratory phases. Three DIR algorithms, optical flow (OF), diffeomorphic morphons (DM), and diffeomorphic demons (DD) were validated using a 4D thorax model, consisting of a 4D CT image dataset, along with associated landmarks delineated by a radiologist. Image differences between the deformed and the target images were used to evaluate the degree of registration accuracy of the three DIR algorithms. In the validation of the DIR algorithms, the average target registration error (TRE) for normal end-expiration-to-end-inspiration registration with one standard deviation (SD) for the DIR algorithms was 1.6 ± 0.9 mm (maximum 3.1 mm) for OF, 1.4 ± 0.6 mm (maximum 3.3 mm) for DM, and 1.4 ± 0.7 mm (maximum 3.3 mm) for DD, indicating registration errors were within two voxels. As a reference, the median value of TRE between 0 and 50% phases with rigid registration only was 5.0 mm with one SD of 2.5 mm and the maximum value of 12.0 mm. For the OF algorithm, 81% of voxels were within a difference of 50 HU, and 93% of the voxels were within 100 HU. For the DM algorithm, 69% of voxels were within 50 HU, and 87% within 100 HU. For the DD algorithm, 71% of the voxels were within 50 HU, and 87% within a difference of 100 HU. These data suggest that the three DIR methods perform accurate registrations in the thorax region. The mean TRE for all three DIR methods was less than two voxels suggesting that the registration performed by all methods are equally accurate in the thorax.
authors: Division of Radiation Oncology, H. Lee Moffitt Cancer Center, Tampa, FL, USA.
authors: Kujtim
authors: K
authors: Latifi
authors: Geoffrey
authors: G
authors: Zhang
authors: Marnix
authors: M
authors: Stawicki
authors: Wouter
authors: W
authors: van Elmpt
authors: Andre
authors: A
authors: Dekker
authors: Kenneth
authors: K
authors: Forster
mesh_terms: D000465:Algorithms; D006801:Humans; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D013902:Radiography, Thoracic / Q000379:methods*; D015203:Reproducibility of Results; D055425:Respiratory-Gated Imaging Techniques / Q000379:methods; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D014057:Tomography, X-Ray Computed / Q000379:methods*