Literature DB >> 34029189

High Pitch Helical CT Reconstruction.

John W Hayes, Juan Montoya, Adam Budde, Chengzhu Zhang, Yinsheng Li, Ke Lia, Jiang Hsieh, Guang-Hong Chen.   

Abstract

To avoid severe limited-view artifacts in reconstructed CT images, current multi-row detector CT (MDCT) scanners with a single x-ray source-detector assembly need to limit table translation speeds such that the pitch p (viz., normalized table translation distance per gantry rotation) is lower than 1.5. When p > 1.5, it remains an open question whether one can reconstruct clinically useful helical CT images without severe artifacts. In this work, we show that a synergistic use of advanced techniques in conventional helical filtered backprojection, compressed sensing, and more recent deep learning methods can be properly integrated to enable accurate reconstruction up to p = 4 without significant artifacts for single source MDCT scans.

Entities:  

Year:  2021        PMID: 34029189     DOI: 10.1109/TMI.2021.3083210

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  1 in total

1.  Reconstruction of three-dimensional tomographic patient models for radiation dose modulation in CT from two scout views using deep learning.

Authors:  Juan C Montoya; Chengzhu Zhang; Yinsheng Li; Ke Li; Guang-Hong Chen
Journal:  Med Phys       Date:  2022-01-06       Impact factor: 4.506

  1 in total

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