Single-projection based volumetric image reconstruction and 3D tumor localization in real time for lung cancer radiotherapy

Ruijiang Li; Xun Jia; John H. Lewis; Xuejun Gu; Michael Folkerts; Chunhua Men; Steve B. Jiang

doi:10.1007/978-3-642-15711-0_56

Single-projection based volumetric image reconstruction and 3D tumor localization in real time for lung cancer radiotherapy

Ruijiang Li, Xun Jia, John H. Lewis, Xuejun Gu, Michael Folkerts, Chunhua Men, Steve B. Jiang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

18 Scopus citations

Abstract

We have developed an algorithm for real-time volumetric image reconstruction and 3D tumor localization based on a single x-ray projection image. We first parameterize the deformation vector fields (DVF) of lung motion by principal component analysis (PCA). Then we optimize the DVF applied to a reference image by adapting the PCA coefficients such that the simulated projection of the reconstructed image matches the measured projection. The algorithm was tested on a digital phantom as well as patient data. The average relative image reconstruction error and 3D tumor localization error for the phantom is 7.5% and 0.9 mm, respectively. The tumor localization error for patient is ~2 mm. The computation time of reconstructing one volumetric image from each projection is around 0.2 and 0.3 seconds for phantom and patient, respectively, on an NVIDIA C1060 GPU. Clinical application can potentially lead to accurate 3D tumor tracking from a single imager.

Original language	English (US)
Title of host publication	Medical Image Computing and Computer-Assisted Intervention, MICCAI2010 - 13th International Conference, Proceedings
Pages	449-456
Number of pages	8
Edition	PART 3
DOIs	https://doi.org/10.1007/978-3-642-15711-0_56
State	Published - 2010
Event	13th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2010 - Beijing, China Duration: Sep 20 2010 → Sep 24 2010

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 3
Volume	6363 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	13th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2010
Country/Territory	China
City	Beijing
Period	9/20/10 → 9/24/10

Keywords

GPU
image reconstruction
lung cancer radiotherapy
lung motion
tumor localization

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-642-15711-0_56

Cite this

Li, R., Jia, X., Lewis, J. H., Gu, X., Folkerts, M., Men, C., & Jiang, S. B. (2010). Single-projection based volumetric image reconstruction and 3D tumor localization in real time for lung cancer radiotherapy. In Medical Image Computing and Computer-Assisted Intervention, MICCAI2010 - 13th International Conference, Proceedings (PART 3 ed., pp. 449-456). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6363 LNCS, No. PART 3). https://doi.org/10.1007/978-3-642-15711-0_56

Single-projection based volumetric image reconstruction and 3D tumor localization in real time for lung cancer radiotherapy. / Li, Ruijiang; Jia, Xun; Lewis, John H. et al.
Medical Image Computing and Computer-Assisted Intervention, MICCAI2010 - 13th International Conference, Proceedings. PART 3. ed. 2010. p. 449-456 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6363 LNCS, No. PART 3).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Li, R, Jia, X, Lewis, JH, Gu, X, Folkerts, M, Men, C & Jiang, SB 2010, Single-projection based volumetric image reconstruction and 3D tumor localization in real time for lung cancer radiotherapy. in Medical Image Computing and Computer-Assisted Intervention, MICCAI2010 - 13th International Conference, Proceedings. PART 3 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 3, vol. 6363 LNCS, pp. 449-456, 13th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2010, Beijing, China, 9/20/10. https://doi.org/10.1007/978-3-642-15711-0_56

Li R, Jia X, Lewis JH, Gu X, Folkerts M, Men C et al. Single-projection based volumetric image reconstruction and 3D tumor localization in real time for lung cancer radiotherapy. In Medical Image Computing and Computer-Assisted Intervention, MICCAI2010 - 13th International Conference, Proceedings. PART 3 ed. 2010. p. 449-456. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 3). doi: 10.1007/978-3-642-15711-0_56

Li, Ruijiang ; Jia, Xun ; Lewis, John H. et al. / Single-projection based volumetric image reconstruction and 3D tumor localization in real time for lung cancer radiotherapy. Medical Image Computing and Computer-Assisted Intervention, MICCAI2010 - 13th International Conference, Proceedings. PART 3. ed. 2010. pp. 449-456 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 3).

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AB - We have developed an algorithm for real-time volumetric image reconstruction and 3D tumor localization based on a single x-ray projection image. We first parameterize the deformation vector fields (DVF) of lung motion by principal component analysis (PCA). Then we optimize the DVF applied to a reference image by adapting the PCA coefficients such that the simulated projection of the reconstructed image matches the measured projection. The algorithm was tested on a digital phantom as well as patient data. The average relative image reconstruction error and 3D tumor localization error for the phantom is 7.5% and 0.9 mm, respectively. The tumor localization error for patient is ~2 mm. The computation time of reconstructing one volumetric image from each projection is around 0.2 and 0.3 seconds for phantom and patient, respectively, on an NVIDIA C1060 GPU. Clinical application can potentially lead to accurate 3D tumor tracking from a single imager.

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Single-projection based volumetric image reconstruction and 3D tumor localization in real time for lung cancer radiotherapy

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