CT image reconstruction on a low dimensional manifold

Abstract

The patch manifold of a natural image has a low dimensional struc-ture and accommodates rich structural information. Inspired by the recent work of the low-dimensional manifold model (LDMM), we apply the LDMM for regularizing X-ray computed tomography (CT) image reconstruction. This proposed method recovers detailed structural information of images, signifi-cantly enhancing spatial and contrast resolution of CT images. Both numer-ically simulated data and clinically experimental data are used to evaluate the proposed method. The comparative studies are also performed over the simultaneous algebraic reconstruction technique (SART) incorporated the to-tal variation (TV) regularization to demonstrate the merits of the proposed method. Results indicate that the LDMM-based method enables a more accu-rate image reconstruction with high fidelity and contrast resolution.