Distortion correction and calibration of intra-operative spine X-ray images using a constrained DLT algorithm

A fully automatic fiducial detection and correspondence establishing method for online C-arm calibration

PURPOSE

Online C-arm calibration with a mobile fiducial cage plays an essential role in various image-guided interventions. However, it is challenging to develop a fully automatic approach, which requires not only an accurate detection of fiducial projections but also a robust 2D-3D correspondence establishment.

METHODS

We propose a novel approach for online C-arm calibration with a mobile fiducial cage. Specifically, a novel mobile calibration cage embedded with 16 fiducials is designed, where the fiducials are arranged to form 4 line patterns with different cross-ratios. Then, an auto-context-based detection network (ADNet) is proposed to perform an accurate and robust detection of 2D projections of those fiducials in acquired C-arm images. Subsequently, we present a cross-ratio consistency-based 2D-3D correspondence establishing method to automatically match the detected 2D fiducial projections with those 3D fiducials, allowing for an accurate online C-arm calibration.

RESULTS

We designed and conducted comprehensive experiments to evaluate the proposed approach. For automatic detection of 2D fiducial projections, the proposed ADNet achieved a mean point-to-point distance of 0.65 ± 1.33 pixels. Additionally, the proposed C-arm calibration approach achieved a mean re-projection error of 1.01 ± 0.63 pixels and a mean point-to-line distance of 0.22 ± 0.12  mm. When the proposed C-arm calibration approach was applied to downstream tasks involving landmark and surface model reconstruction, sub-millimeter accuracy was achieved.

CONCLUSION

In summary, we developed a novel approach for online C-arm calibration. Both qualitative and quantitative results of comprehensive experiments demonstrated the accuracy and robustness of the proposed approach. Our approach holds potentials for various image-guided interventions.

Perspective pinhole model with planar source for augmented reality surgical navigation based on C-arm imaging

PURPOSE

For augmented reality surgical navigation based on C-arm imaging, accuracy of the overlaid augmented reality onto the X-ray image is imperative. However, overlay displacement is generated when a conventional pinhole model describing a geometric relationship of a normal camera is adopted for C-arm calibration. Thus, a modified model for C-arm calibration is proposed to reduce this displacement, which is essential for accurate surgical navigation.

METHOD

Based on the analysis of displacement pattern generated for three-dimensional objects, we assumed that displacement originated by moving the X-ray source position according to the depth. In the proposed method, X-ray source movement was modeled as variable intrinsic parameters and represented in the pinhole model by replacing the point source with a planar source.

RESULTS

The improvement which represents a reduced displacement was verified by comparing overlay accuracy for augmented reality surgical navigation between the conventional and proposed methods. The proposed method achieved more accurate overlay on the X-ray image in spatial position as well as depth of the object volume.

CONCLUSION

We validated that intrinsic parameters that describe the source position were dependent on depth for a three-dimensional object and showed that displacement can be reduced and become independent of depth by using the proposed planar source model.

Multimodality calibration for simultaneous fluoroscopic and nuclear imaging

Background

Simultaneous real-time fluoroscopic and nuclear imaging could benefit image-guided (oncological) procedures. To this end, a hybrid modality is currently being developed by our group, by combining a c-arm with a gamma camera and a four-pinhole collimator. Accurate determination of the system parameters that describe the position of the x-ray tube, x-ray detector, gamma camera, and collimators is crucial to optimize image quality. The purpose of this study was to develop a calibration method that estimates the system parameters used for reconstruction.

A multimodality phantom consisting of five point sources was created. First, nuclear and fluoroscopic images of the phantom were acquired at several distances from the image intensifier. The system parameters were acquired using physical measurement, and multimodality images of the phantom were reconstructed. The resolution and co-registration error of the point sources were determined as a measure of image quality. Next, the system parameters were estimated using a calibration method, which adjusted the parameters in the reconstruction algorithm, until the resolution and co-registration were optimized. For evaluation, multimodality images of a second set of phantom acquisitions were reconstructed using calibrated parameter sets. Subsequently, the resolution and co-registration error of the point sources were determined as a measure of image quality. This procedure was performed five times for different noise simulations. In addition, simultaneously acquired fluoroscopic and nuclear images of two moving syringes were obtained with parameter sets from before and after calibration.

Results

The mean FWHM was significantly lower after calibration than before calibration for 21 out of 25 point sources. The mean co-registration error was significantly lower after calibration than before calibration for all point sources. The simultaneously acquired fluoroscopic and nuclear images showed improved co-registration after calibration as compared with before calibration.

Conclusions

A calibration method was presented that improves the resolution and co-registration of simultaneously acquired hybrid fluoroscopic and nuclear images by estimating the geometric parameter set as compared with a parameter set acquired by direct physical measurement.

Electronic supplementary material

The online version of this article (doi:10.1186/s40658-016-0156-1) contains supplementary material, which is available to authorized users.