Optimization of the geometry and speed of a moving blocker system for cone‐beam computed tomography scatter correction

Abstract

Purpose X-ray scatter is a significant barrier to image quality improvements in cone-beam computed tomography (CBCT). A moving blocker-based strategy was previously proposed to simultaneously estimate scatter and reconstruct the complete volume within the field of view (FOV) from a single CBCT scan. A blocker consisting of lead stripes is inserted between the x-ray source and the imaging object, and moves back and forth along the rotation axis during gantry rotation. While promising results were obtained in our previous studies, the geometric design and moving speed of the blocker were set empirically. The goal of this work is to optimize the geometry and speed of the moving block system. Methods Performance of the blocker was examined through Monte Carlo (MC) simulation and experimental studies with various geometry designs and moving speeds. All hypothetical designs employed an anthropomorphic pelvic phantom. The scatter estimation accuracy was quantified by using lead stripes ranging from 5 to 100 pixels on the detector plane. An iterative reconstruction based on total variation minimization was used to reconstruct CBCT images from unblocked projection data after scatter correction. The reconstructed image was evaluated under various combinations of lead strip width and interspace (ranging from 10 to 60 pixels) and different moving speed (ranging from 1 to 30 pixels per projection). Results MC simulation showed that the scatter estimation error varied from 0.8% to 5.8%. Phantom experiment showed that CT number error in the reconstructed CBCT images varied from 13 to 35. Highest reconstruction accuracy was achieved when the strip width was 20 pixels and interspace was 60 pixels and the moving speed was 15 pixels per projection. Conclusions Scatter estimation can be achieved in a large range of lead strip width and interspace combinations. The moving speed does not have a very strong effect on reconstruction result if it is above 5 pixels per projection. Geometry design of the blocker affected image reconstruction accuracy more. The optimal geometry of the blocker has a strip width of 20 pixels and an interspace three times the strip width, which means 25% detector is covered by the blocker, while the optimal moving speed is 15 pixels per projection.

SparseCT: System concept and design of multislit collimators

“…Instead of moving the beam blocker during the gantry rotation, they left the beam blocker stationary in the beam, but positioned it asymmetrically with respect to the central longitudinal line of the detector, so that at least one ray from its conjugate ray pair can be measured on the detector. Chen et al . also investigated a beam‐interrupting blocker for cone‐beam CT and optimized the blocker design in terms of slit separation and moving speed.…”

“…The drawback of this scheme is that current clinical CT systems cannot pulse the x‐ray source on the needed millisecond timeframe, since the thermal inertia of the cathode cannot be overcome quickly enough. For this reason, several previous works have proposed a different undersampling scheme that partially blocks the beam between the x‐ray tube and the patient to undersample along the detector row direction within each view . SparseCT is one such undersampling approach.…”

A weighted rebinned backprojection‐filtration algorithm from partially beam‐blocked data for a single‐scan cone‐beam CT with hybrid type scatter correction

“…The convolution‐based method is computationally efficient, but the kernel must be predefined to be used and the results are sensitive to the kernel parameters . The measurement‐based methods typically use x‐ray beam‐blockers or beam stopper array . The measurement‐based methods are simple and efficient, and can achieve accurate scatter estimation without a prior knowledge of the target object.…”

“…However, secondary effects due to modulator penumbra and beam hardening may influence the scatter distribution. Recently, object model‐based approaches were introduced for scatter correction using energy‐resolved reprojection technique . Nevertheless, segmentation involving complex materials and structures may become a very challenging work.…”

“…[12][13][14][15] The measurement-based methods typically use x-ray beam-blockers or beam stopper array. [16][17][18][19][20][21][22][23][24][25] The measurement-based methods are simple and efficient, and can achieve accurate scatter estimation without a prior knowledge of the target object. However, they usually end up with a problem of insufficient primary signals for accurate image reconstruction.…”