Cone-beam CT sequence scan reconstruction with improved dose usage and scan coverage

• Published in: 2009 IEEE Nuclear Science Symposium Conference Record (NSS/MIC) pp. 3759 - 3763
• Main Authors: Grimmer, Rainer, Berkus, Timo, Oelhafen, Markus, Kunz, Patrik, Kachelriess, Marc
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.10.2009
• Subjects: Computed tomography; Cone-beam Computed tomography (CBCT); Detectors; Extended z-Range; Geometry; Image quality; Image reconstruction; Noise measurement; Noise reduction; Nuclear and plasma sciences; Performance evaluation; Radio frequency; Sequence Scan; Spatial resolution
• ISBN: 9781424439614; 1424439612
• ISSN: 1082-3654; 2577-0829
• DOI: 10.1109/NSSMIC.2009.5401883

For circular cone-beam CT often one scan covers not the complete z-range of interest. If this is the case two or more circle scans are made. These sequence scans are typically reconstructed by separately reconstructing each circle scan followed by combining the resulting partial volumes. This image-based concatenation method uses only those data that are needed for each partial volume, the contribution of rays to neighboring volumes are ignored, redundancies are not used, and dose is wasted. Therefore an algorithm that uses all rays that run through a voxel by appropriately weighting the rays followed by filtered backprojection was developed and evaluated. This leads to improved dose usage and increases the overlap region of neighboring volumes, potentially leading to reduced artifacts in this region. Alternatively, our approach allows to increase the table increment between adjacent circle acquisitions, and thereby the scan coverage, without impairing image quality or increasing dose. To evaluate our method we use the geometry of the Varian OBI flat panel detector CT scanner. Simulated and measured data are processed at varying table increment values and an evaluation of image noise, spatial resolution and artifacts has been performed. The method shows good image quality on simulated phantom data as well as on clinical patient data. In this paper the algorithm demonstrates its ability to extend the z-range of sequence scans and to improve the image quality in the overlap region and turns out to be usable on devices in the clinical practice.