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Title: 4D cone beam CT via spatiotemporal tensor framelet

Abstract

Purpose: On-board 4D cone beam CT (4DCBCT) offers respiratory phase-resolved volumetric imaging, and improves the accuracy of target localization in image guided radiation therapy. However, the clinical utility of this technique has been greatly impeded by its degraded image quality, prolonged imaging time, and increased imaging dose. The purpose of this letter is to develop a novel iterative 4DCBCT reconstruction method for improved image quality, increased imaging speed, and reduced imaging dose. Methods: The essence of this work is to introduce the spatiotemporal tensor framelet (STF), a high-dimensional tensor generalization of the 1D framelet for 4DCBCT, to effectively take into account of highly correlated and redundant features of the patient anatomy during respiration, in a multilevel fashion with multibasis sparsifying transform. The STF-based algorithm is implemented on a GPU platform for improved computational efficiency. To evaluate the method, 4DCBCT full-fan scans were acquired within 30 s, with a gantry rotation of 200°; STF is also compared with a state-of-art reconstruction method via spatiotemporal total variation regularization. Results: Both the simulation and experimental results demonstrate that STF-based reconstruction achieved superior image quality. The reconstruction of 20 respiratory phases took less than 10 min on an NVIDIA Tesla C2070 GPU card. Themore » STF codes are available at https://sites.google.com/site/spatiotemporaltensorframelet . Conclusions: By effectively utilizing the spatiotemporal coherence of the patient anatomy among different respiratory phases in a multilevel fashion with multibasis sparsifying transform, the proposed STF method potentially enables fast and low-dose 4DCBCT with improved image quality.« less

Authors:
 [1]; ;  [2];  [3]
  1. Departments of Mathematics and Computer Science, and Radiology and Imaging Sciences, Emory University, Atlanta, Georgia 30322 (United States)
  2. Department of Radiation Oncology, Stanford University, Stanford, California 94305 (United States)
  3. Department of Radiological Sciences, University of California, Irvine, California 92697 (United States)
Publication Date:
OSTI Identifier:
22620825
Resource Type:
Journal Article
Journal Name:
Medical Physics
Additional Journal Information:
Journal Volume: 39; Journal Issue: 11; Other Information: (c) 2012 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0094-2405
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; ACCURACY; ALGORITHMS; ANATOMY; BIOMEDICAL RADIOGRAPHY; COMPUTERIZED TOMOGRAPHY; IMAGES; ITERATIVE METHODS; PATIENTS; RADIOTHERAPY

Citation Formats

Gao, Hao, E-mail: hao.gao@emory.edu, Li, Ruijiang, Xing, Lei, and Lin, Yuting. 4D cone beam CT via spatiotemporal tensor framelet. United States: N. p., 2012. Web. doi:10.1118/1.4762288.
Gao, Hao, E-mail: hao.gao@emory.edu, Li, Ruijiang, Xing, Lei, & Lin, Yuting. 4D cone beam CT via spatiotemporal tensor framelet. United States. doi:10.1118/1.4762288.
Gao, Hao, E-mail: hao.gao@emory.edu, Li, Ruijiang, Xing, Lei, and Lin, Yuting. Thu . "4D cone beam CT via spatiotemporal tensor framelet". United States. doi:10.1118/1.4762288.
@article{osti_22620825,
title = {4D cone beam CT via spatiotemporal tensor framelet},
author = {Gao, Hao, E-mail: hao.gao@emory.edu and Li, Ruijiang and Xing, Lei and Lin, Yuting},
abstractNote = {Purpose: On-board 4D cone beam CT (4DCBCT) offers respiratory phase-resolved volumetric imaging, and improves the accuracy of target localization in image guided radiation therapy. However, the clinical utility of this technique has been greatly impeded by its degraded image quality, prolonged imaging time, and increased imaging dose. The purpose of this letter is to develop a novel iterative 4DCBCT reconstruction method for improved image quality, increased imaging speed, and reduced imaging dose. Methods: The essence of this work is to introduce the spatiotemporal tensor framelet (STF), a high-dimensional tensor generalization of the 1D framelet for 4DCBCT, to effectively take into account of highly correlated and redundant features of the patient anatomy during respiration, in a multilevel fashion with multibasis sparsifying transform. The STF-based algorithm is implemented on a GPU platform for improved computational efficiency. To evaluate the method, 4DCBCT full-fan scans were acquired within 30 s, with a gantry rotation of 200°; STF is also compared with a state-of-art reconstruction method via spatiotemporal total variation regularization. Results: Both the simulation and experimental results demonstrate that STF-based reconstruction achieved superior image quality. The reconstruction of 20 respiratory phases took less than 10 min on an NVIDIA Tesla C2070 GPU card. The STF codes are available at https://sites.google.com/site/spatiotemporaltensorframelet . Conclusions: By effectively utilizing the spatiotemporal coherence of the patient anatomy among different respiratory phases in a multilevel fashion with multibasis sparsifying transform, the proposed STF method potentially enables fast and low-dose 4DCBCT with improved image quality.},
doi = {10.1118/1.4762288},
journal = {Medical Physics},
issn = {0094-2405},
number = 11,
volume = 39,
place = {United States},
year = {2012},
month = {11}
}