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Compressed Sensing Based Four Dimensional Cone-Beam Computed Tomography Reconstruction by Continuation Accelerated Nesterov's Descent

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H Zhang

H Zhang*, J Sonke, Netherlands Caner InstituteAmsterdam

TU-A-213CD-7 Tuesday 8:00:00 AM - 9:55:00 AM Room: 213CD

Purpose:
Compressed sensing based cone-beam reconstruction is introduced to reduce streaking artifacts due to under-sampling in four dimensional (4D) cone-beam computed tomography (CBCT). This reconstruction, however, is typically time-consuming, especially for 4D CBCT. We propose a novel approach, which introduces a first-order methods, called continuation accelerated Nesterov's descent, to improve convergence rate.

Methods:
We extract the respiratory signal directly from projections, sort them into ten subsets, and reconstruct each subset into a 3D CBCT by compressed sensing based total-variation minimization. The reconstruction iteration is solved by Nesterov's descent algorithm. In each loop, we adapt the step size by sufficient reducing global Lipschitz constant, and update variants by gradient-mapping parameters to proximal points. The proposed method is assessed by a thorax phantom and a patient, which are scanned with a CBCT scanner. The reconstructed data is compared among FDK algorithm, projection onto convex sets (POCS) which is a steepest decent based optimization, and our method.

Results:
A region of homogeneous voxel values is manually selected, and the root-mean-square-error between CBCT and CT in this region is defined as streaking artifacts. It's reduced 27.2% in phantom data, when our method is compared to traditional FDK methods for 2 minute scan. Correlation ratio between CBCT and CT is increased for 10.2% when our method is compared to FDK for patient data. For the convergence rate, our method only needs 25 iterations to get the same total-variation residual of POCS at 250 iterations. Also for other cut-offs, it seems an order of magnitude faster.

Conclusions:
Our proposed method decreases the streaking artifacts and convergence time in 4D CBCT reconstruction. The image quality assessment suggests that our method has improved image quality and better correlation.

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