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 CBCTimages 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 compared to 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 frame of reference to a wealth of preoperative information that could improve interventional guidance.
The research was supported by the National Institutes of Health (Grant No. R01-CA-127944) and a collaboration with Siemens Healthcare (Erlangen, Germany). The authors thank Dr. Clemens Bulitta, Dr. Rainer Graumann, Dr. Gerhard Kleinszig, and Dr. Christian Schmidgunst (Siemens SP, Erlangen Germany) for collaboration and technical discussion concerning the prototype C-arm. This work benefited from the use of the Insight Segmentation and Registration Toolkit (ITK, U.S. National Library of Medicine).
II.A. Registration method
II.A.1. Demons deformable registration
II.A.2. Techniques for multimodality registration
II.A.3. Iterative intensity matching for CT-CBCT registration
II.B. Experimental methods
II.B.1. Simulation of image intensity errors
II.B.2. Evaluation with alternate image metrics and registration strategies
II.B.3. Performance evaluation in real CT-CBCT data
III.A. Simulation of image intensity errors
III.B. Iterative intensity match
III.B.1. Evolution of intensity matching fits
III.B.2. Effect on computation time
III.B.3. Evaluation with alternate image metrics and registration strategies
III.C. Performance evaluation in real CT-CBCT data
III.C.1. Simple deformations (cases 1–3)
III.C.2. Complex deformations and disease (cases 4–6)
IV. DISCUSSION AND CONCLUSIONS
Data & Media loading...
Article metrics loading...
Full text loading...