Motion Correction

Many imaging systems take several seconds or minutes to scan a patient. Depending on the scan protocol of a C-arm CT or MRI it takes several seconds, while a PET or SPECT scan takes minutes. Patient motion like respiration can cause strong artifacts and motion related blurring in the reconstructed image. The combination of registration technologies to estimate patient or organ motion with motion corrected reconstruction allows to improve image quality of such degrated images.

Chimaera GmbH has a profound background in motion estimation using latest registration technologies as well as in motion correction for Fourier-based and iterative reconstruction. The combination of both technologies allows a customized integration for motion correction into your product.

Features

  • Customized solutions
  • Motion model computation based on a 2D or 3D image sequence using registration technologies
  • Motion model computation based on projection data
  • Motion correction for Fourier-based methods
  • Motion correction for iterative algebraic reconstruction
  • Motion correction for maximum likelihood-based reconstruction
  • Customized integration of the motion correction step into your reconstruction framework
  • Years of experience in motion correction technologies
  • GPU acceleration using CUDA or OpenCL on request
  • Technologies for PET, SPECT, C-arm CT and MRI

Motion Estimation

Due to scan times of several seconds or minutes of some imaging systems (C-Arm CT, PET, SPECT, MR), the scanned subject may move during the data acquisition. The patient or organ motion can be rigid, affine or even non-rigid like the heart motion. To reduce motion related blurring and artifacts in the reconstructed image of a patient, it is crucial to precisely estimate the motion using registration technologies.

Reconstruction

The motion correction step is part of the reconstruction process. The estimated and subject specific motion model is taken into account during the backprojection in the reconstruction. Fourier-based reconstruction methods perform an adapted backprojection using curved ray paths. Iterative reconstruction methods are extended by forward and back-projectors that incoorporate the motion model. Depending on the application, the motion model can be rigid, affine or non-rigid.

Examples and Applications

Cardiac C-Arm CT

A common approach to target a specific cardiac phase is to gate the projection data according to the ECG signal. The gated X-ray data is then used for the image reconstruction. However, this is not very dose efficient since some of the X-ray data is not used. Motion correction allows to increase dose efficiency in cardiac C-arm CT by taking more X-ray data into account that lies outside the target heart phase.

The left image shows a standard FDK reconstruction using 191 ECG-gated projections. The right image has been reconstructed using all 1146 acquired projection images from a C-arm CT scan in combination with motion correction performed during a FDK reconstruction. The images show a single MPR of each reconstructed image. 
The comparison of the two reconstruction approaches in a volume rendering. Again, the left image shows the standard FDK reconstruction using 191 ECG-gated projections, the right image is the result using the motion correction approach with all 1146 acquired projection images from a C-arm CT scan.

Images have been taken from: M. Prümmer: Cardiac C-Arm Computed Tomography: Motion Estimation and Dynamic Reconstruction, PhD Thesis, Universität Erlangen-Nürnberg, 2009.