SUBJECT: Ph.D. Proposal Presentation
BY: Xue Dong
TIME: Thursday, September 26, 2013, 10:00 a.m.
PLACE: Boggs, 3-39
TITLE: Novel Methods for Scatter Correction and Dual Energy Imaging in Cone-beam CT
COMMITTEE: Dr. Lei Zhu, Chair (NRE/MP)
Dr. C.-K. Chris Wang (NRE/MP)
Dr. Timothy H. Fox (NRE/MP/Emory)
Dr. Ioannis Sechopoulos (BME/Emory)
Dr. Xiangyang Tang (Emory)


On-board cone-beam CT (CBCT) is being increasingly implemented on radiation therapy machines for accurate patient positioning and tumor targeting in image-guided radiation therapy (IGRT). Nevertheless, excessive imaging dose from repeated scans and poor image quality mainly due to scatter contamination are the two bottlenecks of cone-beam CT (CBCT) imaging. Compressed sensing (CS) reconstruction algorithms show promises in recovering faithful signals from low-dose projection data, but donít serve well the needs of accurate CBCT imaging if effective scatter correction is not in place. Scatter can be accurately measured and removed using measurement-based methods. However, these approaches are considered unpractical in the conventional FDK reconstruction, due to the inevitable primary loss for scatter measurement. We combine measurement-based scatter correction and CS-based iterative reconstruction algorithm to generate scatter-free images from low-dose data. We distribute blocked areas on the detector where primary signals are considered redundant in a full scan. Scatter distribution is estimated by interpolating/extrapolating measured scatter samples inside blocked areas. CS-based iterative reconstruction is finally carried out on the under-sampled data to obtain scatter-free and low-dose CBCT images.
Dual-energy CT (DECT) is another important application of CBCT. DECT gains diagnostic information on tissue composition and facilities rapid and accurate diagnosis. A generic problem of DECT, however, is that the decomposition process is unstable in the sense that the magnitude of true decomposed signals is significantly reduced due to signal cancellation while the image noise accumulates from the two initial CT images of independent scans. A direct image decomposition, therefore, leads to severe degradation of signal-to-noise ratio (SNR) on the resultant images. Previous noise suppression techniques typically implement the procedures of reconstruction and decomposition sequentially. The problem of noise boost is alleviated by standard noise suppression algorithms at the cost of reduced spatial resolution. In this work, we propose a different method that combines the reconstruction and decomposition of DECT, such that the decomposition step is carried out iteratively. The noise on the two initial CT images from separate scans becomes well correlated, which avoids noise accumulation during the decomposition process.