Maximum Likelihood Estimation of Head Motion Using Epipolar Consistency
Open gantry C-arm systems that are placed within the interventional room enable 3-D imaging and guidance for stroke therapy without patient transfer. This can profit in drastically reduced time-totherapy, however, due to the interventional setting, the data acquisition is comparatively slow. Thus, involuntary patient motion needs to be estimated and compensated to achieve high image quality. Patient motion results in a misalignment of the geometry and the acquired image data. Consistency measures can be used to restore the correct mapping to compensate the motion. They describe constraints on an idealized imaging process which makes them also sensitive to beam hardening, scatter, truncation or overexposure. We propose a probabilistic approach based on the Student’s t-distribution to model image artifacts that affect the consistency measure without sourcing from motion.
Unable to display preview. Download preview PDF.
- 1.Psychogios M, Behme D, Schregel K, et al. One-stop management of acute stroke patients: minimizing door-to-reperfusion times. Stroke. 2017;.Google Scholar
- 2.Müller K, Maier A, Lauritsch G, et al. Image artefact propagation in motion estimation and reconstruction in cardiac C-arm CT. Proc PMB. 2014;.Google Scholar
- 3.Preuhs A, Maier A, Manhart M, et al. Double your views: exploiting symmetry in transmission imaging. Proc MICCAI. 2018;.Google Scholar
- 4.Frysch R, Rose G. Rigid motion compensation in C-arm CT using consistency measure on projection data. Proc MICCAI. 2015;.Google Scholar
- 5.Abdurahman S, Frysch R, Bismark R, et al. Beam hardening correction using cone beam consistency conditions. IEEE Trans med Imaging. 2018;.Google Scholar
- 6.Würfl T, Maaß N, Dennerlein F, et al. Epipolar consistency guided beam hardening reduction-ECC 2. Fully 3D. 2017;.Google Scholar
- 7.Hoffmann M, Würfl T, Maaß N, et al. Empirical scatter correction using the epipolar consistency condition. CT-Meet. 2018;.Google Scholar
- 8.Punzet D, Frysch R, Rose G. Extrapolation of truncated C-arm CT data using grangeat-based consistency measures. CT-Meet. 2018;.Google Scholar
- 9.Preuhs A, Berger M, Xia Y, et al. Over-exposure correction in CT using optimization-based multiple cylinder fitting. Proc BVM. 2015;.Google Scholar
- 10.Debbeler C, N, Elter M, et al. A new CT rawdata redundancy measure applied to automated misalignment correction. Fully 3D. 2013;.Google Scholar
- 11.Aichert A, Berger M, Wang J, et al. Epipolar consistency in transmission imaging. IEEE Trans Med Imaging. 2015;.Google Scholar