Demons deformable registration of CT and cone-beam CT using an iterative intensity matching approach

• Published in: Medical physics (Lancaster) 2011-04, Vol.38 (4), p.1785-1798
• Main Authors: Nithiananthan, Sajendra, Schafer, Sebastian, Uneri, Ali, Mirota, Daniel J., Stayman, J. Webster, Zbijewski, Wojciech, Brock, Kristy K., Daly, Michael J., Chan, Harley, Irish, Jonathan C., Siewerdsen, Jeffrey H.
• Format: Article
• Language: English
• Subjects: 60 APPLIED LIFE SCIENCES; ACCURACY; ALGORITHMS; Anatomy; Computed tomography; computerised tomography; COMPUTERIZED TOMOGRAPHY; Cone beam computed tomography; Cone-Beam Computed Tomography - methods; cone‐beam CT; deformable registration; DEFORMATION; Demons algorithm; HEAD; Humans; IMAGE PROCESSING; Image Processing, Computer-Assisted - methods; image reconstruction; image registration; image‐guided interventions; ITERATIVE METHODS; LINEAR ACCELERATORS; Medical image artifacts; medical image processing; Medical image quality; Medical image reconstruction; Medical imaging; Medical X‐ray imaging; PLANNING; Radiation Imaging Physics; RADIOLOGY AND NUCLEAR MEDICINE; RADIOTHERAPY; Reconstruction; Registration; SIMULATION; SURGERY; Time Factors; Tissues; X RADIATION; X-RAY DIFFRACTION; X‐ray imaging; X‐ray scattering
• ISSN: 0094-2405; 2473-4209; 0094-2405
• DOI: 10.1118/1.3555037

Purpose: A method of intensity-based deformable registration of CT and cone-beam CT (CBCT) images is described, in which intensity correction occurs simultaneously within the iterative registration process. The method preserves the speed and simplicity of the popular Demons algorithm while providing robustness and accuracy in the presence of large mismatch between CT and CBCT voxel values (“intensity”). Methods: A variant of the Demons algorithm was developed in which an estimate of the relationship between CT and CBCT intensity values for specific materials in the image is computed at each iteration based on the set of currently overlapping voxels. This tissue-specific intensity correction is then used to estimate the registration output for that iteration and the process is repeated. The robustness of the method was tested in CBCT images of a cadaveric head exhibiting a broad range of simulated intensity variations associated with x-ray scatter, object truncation, and/or errors in the reconstruction algorithm. The accuracy of CT-CBCT registration was also measured in six real cases, exhibiting deformations ranging from simple to complex during surgery or radiotherapy guided by a CBCT-capable C-arm or linear accelerator, respectively. Results: The iterative intensity matching approach was robust against all levels of intensity variation examined, including spatially varying errors in voxel value of a factor of 2 or more, as can be encountered in cases of high x-ray scatter. Registration accuracy without intensity matching degraded severely with increasing magnitude of intensity error and introduced image distortion. A single histogram match performed prior to registration alleviated some of these effects but was also prone to image distortion and was quantifiably less robust and accurate than the iterative approach. Within the six case registration accuracy study, iterative intensity matching Demons reduced mean TRE to ( 2.5 ± 2.8 )   mm compared to ( 3.5 ± 3.0 )   mm with rigid registration. Conclusions: A method was developed to iteratively correct CT-CBCT intensity disparity during Demons registration, enabling fast, intensity-based registration in CBCT-guided procedures such as surgery and radiotherapy, in which CBCT voxel values may be inaccurate. Accurate CT-CBCT registration in turn facilitates registration of multimodality preoperative image and planning data to intraoperative CBCT by way of the preoperative CT, thereby linking the intraoperative