Literature DB >> 25265926

Top-level design and pilot analysis of low-end CT scanners based on linear scanning for developing countries.

Fenglin Liu1, Hengyong Yu2, Wenxiang Cong3, Ge Wang3.   

Abstract

The goal is to develop new architectures for computed tomography (CT) which are at an ultra-low-cost for developing countries, especially in rural areas. The proposed general scheme is inspired by the recently developed compressive sensing and interior tomography techniques, where the data acquisition system targets a region of interest (ROI) to acquire limited and truncated data. Similar to linear tomosynthesis, the source and detector are translated in opposite directions but in contrast to conventional tomosynthesis, our proposal is for either ROI reconstruction with one or more localized linear scans or global reconstruction by combining multiple ROI reconstructions. In other words, the popular slip ring is replaced by a translation based setup, and the instrumentation cost is reduced by a relaxation of the imaging speed requirement. The various translational scanning modes are theoretically analyzed, and the scanning parameters are optimized. The numerical simulation results from different numbers of linear scans confirm the feasibility of the proposed scheme, and suggest two preferred low-end systems for horizontal and vertical patient positions respectively. Ultra-low-cost x-ray CT is feasible with our proposed combination of linear scanning, compressive sensing, and interior tomography. The proposed architecture can be tailored into permanent, movable, or reconfigurable systems as desirable. Advanced image registration and spectral imaging features can be included as well.

Entities:  

Keywords:  Computed tomography (CT); compressive sensing; interior tomography; linear scanning; low-cost

Mesh:

Year:  2014        PMID: 25265926     DOI: 10.3233/XST-140453

Source DB:  PubMed          Journal:  J Xray Sci Technol        ISSN: 0895-3996            Impact factor:   1.535


  1 in total

1.  Deep learning based image reconstruction algorithm for limited-angle translational computed tomography.

Authors:  Jiaxi Wang; Jun Liang; Jingye Cheng; Yumeng Guo; Li Zeng
Journal:  PLoS One       Date:  2020-01-06       Impact factor: 3.240

  1 in total

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