An improved half-covered helical cone-beam CT reconstruction algorithm based on localized reconstruction filter

Traditional helical cone-beam Computed Tomography (CT) is based on the assumption that the entire cross-section of the scanned object is covered by x-rays at each view angle. Because of the size limitation of planar detector, the traditional helical cone-beam CT scanning is restricted when the cross-section of the object is larger than the field of view (FOV) of the CT system. The helical cone-beam CT scanning based on FOV half-covered can almost double the FOV, whose mechanism is simple and the scanning efficiency is the same as that of traditional helical cone-beam CT. During reconstruction, the extended helical cone-beam FDK algorithm (called half-covered helical FDK for short) is developed, and the computational efficiency of this algorithm is high. But the reconstruction image has truncation error. Regarding this problem, this paper extends the idea of 2D local reconstruction to 3D half-covered helical cone-beam CT, and develops an improved half-covered helical cone-beam CT reconstruction algorithm based on localized reconstruction filter. Experimental results indicate that the presented algorithm well solves the truncation error of the half-covered helical FDK algorithm, improves the quality of the reconstruction image. And for the noise projection data, the presented algorithm can suppress noise and get better results. Moreover, the reconstruction time is much less.