UCL logo

UCL Discovery

UCL home » Library Services » Electronic resources » UCL Discovery

Automatic phase determination for retrospectively gated cardiac CT.

Manzke, R; Köhler, T; Nielsen, T; Hawkes, D; Grass, M; (2004) Automatic phase determination for retrospectively gated cardiac CT. Med Phys , 31 (12) pp. 3345-3362. 10.1118/1.1791351.

Full text not available from this repository.


The recent improvements in CT detector and gantry technology in combination with new heart rate adaptive cone beam reconstruction algorithms enable the visualization of the heart in three dimensions at high spatial resolution. However, the finite temporal resolution still impedes the artifact-free reconstruction of the heart at any arbitrary phase of the cardiac cycle. Cardiac phases must be found during which the heart is quasistationary to obtain outmost image quality. It is challenging to find these phases due to intercycle and patient-to-patient variability. Electrocardiogram (ECG) information does not always represent the heart motion with an adequate accuracy. In this publication, a simple and efficient image-based technique is introduced which is able to deliver stable cardiac phases in an automatic and patient-specific way. From low-resolution four-dimensional data sets, the most stable phases are derived by calculating the object similarity between subsequent phases in the cardiac cycle. Patient-specific information about the object motion can be determined and resolved spatially. This information is used to perform optimized high-resolution reconstructions at phases of little motion. Results based on a simulation study and three real patient data sets are presented. The projection data were generated using a 16-slice cone beam CT system in low-pitch helical mode with parallel ECG recording.

Type: Article
Title: Automatic phase determination for retrospectively gated cardiac CT.
Location: United States
DOI: 10.1118/1.1791351
Keywords: Algorithms, Artifacts, Electrocardiography, Heart, Humans, Imaging, Three-Dimensional, Movement, Pattern Recognition, Automated, Radiographic Image Enhancement, Radiographic Image Interpretation, Computer-Assisted, Reproducibility of Results, Retrospective Studies, Sensitivity and Specificity, Subtraction Technique, Tomography, Spiral Computed
UCL classification: UCL > School of BEAMS > Faculty of Engineering Science
UCL > School of BEAMS > Faculty of Engineering Science > Medical Physics and Bioengineering
URI: http://discovery.ucl.ac.uk/id/eprint/157868
Downloads since deposit
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item