Lung deformation estimation and four-dimensional CT lung reconstruction.

Sheng Xu, Russell H Taylor, Gabor Fichtinger, Kevin Cleary

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Four-dimensional (4D) computed tomography (CT) image acquisition is a useful technique in radiation treatment planning and interventional radiology in that it can account for respiratory motion of lungs. Current 4D lung reconstruction techniques have limitations in either spatial or temporal resolution. In addition, most of these techniques rely on auxiliary surrogates to relate the time of CT scan to the patient's respiratory phase. In this paper, we propose a novel 4D CT lung reconstruction and deformation estimation algorithm. Our algorithm is purely image based. The algorithm can reconstruct high quality 4D images even if the original images are acquired under irregular respiratory motion. The algorithm is validated using synthetic 4D lung data. Experimental results from a swine study data are also presented.

Original languageEnglish (US)
Title of host publicationMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Pages312-319
Number of pages8
Volume8
EditionPt 2
StatePublished - 2005

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    Xu, S., Taylor, R. H., Fichtinger, G., & Cleary, K. (2005). Lung deformation estimation and four-dimensional CT lung reconstruction. In Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention (Pt 2 ed., Vol. 8, pp. 312-319)