Abstract

A novel motion correction algorithm for X-ray lung CT imaging has been developed recently. It was designed to perform for routine chest or thorax CT scans without gating, namely axial or helical scans with pitch around 1.0. The algorithm makes use of two conjugate partial angle reconstruction images for motion estimation via non-rigid registration which is followed by a motion compensated reconstruction. Differently from other conventional approaches, no segmentation is adopted in motion estimation. This makes motion estimation of various fine lung structures possible. The aim of this study is to explore the performance of the proposed method in correcting the lung motion artifacts which arise even under routine CT scans with breath-hold. The artifacts are known to mimic various lung diseases, so it is of great interest to address the problem. For that purpose, a moving phantom experiment and clinical study (seven cases) were conducted. We selected the entropy and positivity as figure of merits to compare the reconstructed images before and after the motion correction. Results of both phantom and clinical studies showed a statistically significant improvement by the proposed method, namely up to 53.6% (p < 0.05) and up to 35.5% (p < 0.05) improvement by means of the positivity measure, respectively. Images of the proposed method show significantly reduced motion artifacts of various lung structures such as lung parenchyma, pulmonary vessels, and airways which are prominent in FBP images. Results of two exemplary cases also showed great potential of the proposed method in correcting motion artifacts of the aorta which is known to mimic aortic dissection. Compared to other approaches, the proposed method provides an excellent performance and a fully automatic workflow. In addition, it has a great potential to handle motions in wide range of organs such as lung structures and the aorta. We expect that this would pave a way toward innovations in chest and thorax CT imaging.

Highlights

  • A novel motion correction algorithm for X-ray lung CT imaging has been developed recently

  • The aim of our study is to explore the capability of SCULLI-TX in correcting motion artifacts of lung and thoracic structures which arise even under routine CT scans with breath-hold

  • To explore the capability of motion correction in other thoracic structures such as the aorta and the superior vena cava (SVC), we investigated the images of FBP and SCULLI-TX qualitatively

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Summary

Introduction

A novel motion correction algorithm for X-ray lung CT imaging has been developed recently. The aim of this study is to explore the performance of the proposed method in correcting the lung motion artifacts which arise even under routine CT scans with breath-hold. Unlike the ­idea[7] adopting a pure imagebased metric and considering only rigid motion, we make use of two reference images and estimate non-rigid motion These images could be complete or incomplete depending on the target organ or scan c­ onditions[8,9]. Since we have no segmentation step, motion of all edges in PAR images is measured This way we can deal with motion of various lung structures such as lung parenchyma, pulmonary vessels and airways. Please refer to the previous ­works[8,9,15]

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