title: Cardiac C-arm CT: a unified framework for motion estimation and dynamic CT.
abstract: Generating 3-D images of the heart during interventional procedures is a significant challenge. In addition to real time fluoroscopy, angiographic C-arm systems can also now be used to generate 3-D/4-D CT images on the same system. One protocol for cardiac CT uses ECG triggered multisweep scans. A 3-D volume of the heart at a particular cardiac phase is then reconstructed by applying Feldkamp (FDK) reconstruction to the projection images with retrospective ECG gating. In this work we introduce a unified framework for heart motion estimation and dynamic cone-beam reconstruction using motion corrections. The benefits of motion correction are 1) increased temporal and spatial resolution by removing cardiac motion which may still exist in the ECG gated data sets and 2) increased signal-to-noise ratio (SNR) by using more projection data than is used in standard ECG gated methods. Three signal-enhanced reconstruction methods are introduced that make use of all of the acquired projection data to generate a 3-D reconstruction of the desired cardiac phase. The first averages all motion corrected back-projections; the second and third perform a weighted averaging according to 1) intensity variations and 2) temporal distance relative to a time resolved and motion corrected reference FDK reconstruction. In a comparison study seven methods are compared: nongated FDK, ECG-gated FDK, ECG-gated, and motion corrected FDK, the three signal-enhanced approaches, and temporally aligned and averaged ECG-gated FDK reconstructions. The quality measures used for comparison are spatial resolution and SNR. Evaluation is performed using phantom data and animal models. We show that data driven and subject-specific motion estimation combined with motion correction can decrease motion-related blurring substantially. Furthermore, SNR can be increased by up to 70% while maintaining spatial resolution at the same level as is provided by the ECG-gated FDK. The presented framework provides excellent image quality for cardiac C-arm CT.
authors.affiliation: Chair of Pattern Recognition, FA-University Erlangen-Nuremberg, 91054 Nuremberg, Germany. pruemmer@informatik.uni-erlangen.de
authors.forename: Marcus
authors.initials: M
authors.lastname: Prümmer
authors.forename: Joachim
authors.initials: J
authors.lastname: Hornegger
authors.forename: Guenter
authors.initials: G
authors.lastname: Lauritsch
authors.forename: Lars
authors.initials: L
authors.lastname: Wigström
authors.forename: Erin
authors.initials: E
authors.lastname: Girard-Hughes
authors.forename: Rebecca
authors.initials: R
authors.lastname: Fahrig
mesh_terms: D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D054893:Cone-Beam Computed Tomography / Q000379:methods*; D004562:Electrocardiography; D006321:Heart / Q000000981:diagnostic imaging / Q000502:physiology; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D009038:Motion; D019047:Phantoms, Imaging; D012815:Signal Processing, Computer-Assisted; D025321:Surgery, Computer-Assisted / Q000379:methods; D013552:Swine