title: Multi-resolution statistical image reconstruction for mitigation of truncation effects: application to cone-beam CT of the head.
abstract: A prototype cone-beam CT (CBCT) head scanner featuring model-based iterative reconstruction (MBIR) has been recently developed and demonstrated the potential for reliable detection of acute intracranial hemorrhage (ICH), which is vital to diagnosis of traumatic brain injury and hemorrhagic stroke. However, data truncation (e.g. due to the head holder) can result in artifacts that reduce image uniformity and challenge ICH detection. We propose a multi-resolution MBIR method with an extended reconstruction field of view (RFOV) to mitigate truncation effects in CBCT of the head. The image volume includes a fine voxel size in the (inner) nontruncated region and a coarse voxel size in the (outer) truncated region. This multi-resolution scheme allows extension of the RFOV to mitigate truncation effects while introducing minimal increase in computational complexity. The multi-resolution method was incorporated in a penalized weighted least-squares (PWLS) reconstruction framework previously developed for CBCT of the head. Experiments involving an anthropomorphic head phantom with truncation due to a carbon-fiber holder were shown to result in severe artifacts in conventional single-resolution PWLS, whereas extending the RFOV within the multi-resolution framework strongly reduced truncation artifacts. For the same extended RFOV, the multi-resolution approach reduced computation time compared to the single-resolution approach (viz. time reduced by 40.7%, 83.0%, and over 95% for an image volume of 6003, 8003, 10003voxels). Algorithm parameters (e.g. regularization strength, the ratio of the fine and coarse voxel size, and RFOV size) were investigated to guide reliable parameter selection. The findings provide a promising method for truncation artifact reduction in CBCT and may be useful for other MBIR methods and applications for which truncation is a challenge.
authors.affiliation: Department of Biomedical Engineering, Johns Hopkins University, Baltimore MD 21205, USA.
authors.forename: Hao
authors.initials: H
authors.lastname: Dang
authors.forename: J Webster
authors.initials: JW
authors.lastname: Stayman
authors.forename: Alejandro
authors.initials: A
authors.lastname: Sisniega
authors.forename: Wojciech
authors.initials: W
authors.lastname: Zbijewski
authors.forename: Jennifer
authors.initials: J
authors.lastname: Xu
authors.forename: Xiaohui
authors.initials: X
authors.lastname: Wang
authors.forename: David H
authors.initials: DH
authors.lastname: Foos
authors.forename: Nafi
authors.initials: N
authors.lastname: Aygun
authors.forename: Vassilis E
authors.initials: VE
authors.lastname: Koliatsos
authors.forename: Jeffrey H
authors.initials: JH
authors.lastname: Siewerdsen
mesh_terms: D000465:Algorithms; D016477:Artifacts; D054893:Cone-Beam Computed Tomography / Q000295:instrumentation / Q000379:methods*; D006257:Head / Q000000981:diagnostic imaging*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008962:Models, Theoretical; D019047:Phantoms, Imaging