Automatic detection of head refixation errors in fractionated stereotactic radiotherapy (FSR)

S. Li; J. Geng; D. Liu; D. Rigamonti; L. Kleinberg; S. He; T. DeWeese

Automatic detection of head refixation errors in fractionated stereotactic radiotherapy (FSR)

S. Li, J. Geng, D. Liu, D. Rigamonti, L. Kleinberg, S. He, T. DeWeese

School of Medicine

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

2 Scopus citations

Abstract

Patient surface images are acquired using a novel 3D camera when the patient is at the CT-simulation position and after setup for fractionated stereotactic treatment. The simulation and treatment images are aligned through an initial registration using several feature points followed by a refined automatic matching process using an iterative-closest-point mapping-align algorithm. All of the video-surface images could be automatically transformed to the machine coordinate according to the calibration file obtained from a template image. Phantom tests have demonstrated that we can capture surface images of patients in a second with spatial resolution of sub-millimeter. A millimeter shift and one-degree rotation relative to the treatment machine can be accurately detected. The entire process takes about two minutes. Our primary result on patients involved in a clinical trial is very promising. This research is partially supported by INH Grant 1R43CA91690-01 and NIH CA88843.

Original language	English (US)
Title of host publication	2004 2nd IEEE International Symposium on Biomedical Imaging
Subtitle of host publication	Macro to Nano
Pages	284-287
Number of pages	4
State	Published - 2004
Event	2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano - Arlington, VA, United States Duration: Apr 15 2004 → Apr 18 2004

Publication series

Name	2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano
Volume	1

Other

Other	2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano
Country/Territory	United States
City	Arlington, VA
Period	4/15/04 → 4/18/04

ASJC Scopus subject areas

General Engineering

Cite this

Automatic detection of head refixation errors in fractionated stereotactic radiotherapy (FSR). / Li, S.; Geng, J.; Liu, D. et al.
2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano. 2004. p. 284-287 (2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano; Vol. 1).

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

Li, S, Geng, J, Liu, D, Rigamonti, D , Kleinberg, L, He, S & DeWeese, T 2004, Automatic detection of head refixation errors in fractionated stereotactic radiotherapy (FSR). in 2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano. 2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano, vol. 1, pp. 284-287, 2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano, Arlington, VA, United States, 4/15/04.

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title = "Automatic detection of head refixation errors in fractionated stereotactic radiotherapy (FSR)",

abstract = "Patient surface images are acquired using a novel 3D camera when the patient is at the CT-simulation position and after setup for fractionated stereotactic treatment. The simulation and treatment images are aligned through an initial registration using several feature points followed by a refined automatic matching process using an iterative-closest-point mapping-align algorithm. All of the video-surface images could be automatically transformed to the machine coordinate according to the calibration file obtained from a template image. Phantom tests have demonstrated that we can capture surface images of patients in a second with spatial resolution of sub-millimeter. A millimeter shift and one-degree rotation relative to the treatment machine can be accurately detected. The entire process takes about two minutes. Our primary result on patients involved in a clinical trial is very promising. This research is partially supported by INH Grant 1R43CA91690-01 and NIH CA88843.",

author = "S. Li and J. Geng and D. Liu and D. Rigamonti and L. Kleinberg and S. He and T. DeWeese",

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AU - Li, S.

AU - Geng, J.

AU - Liu, D.

AU - Rigamonti, D.

AU - Kleinberg, L.

AU - He, S.

AU - DeWeese, T.

PY - 2004

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AB - Patient surface images are acquired using a novel 3D camera when the patient is at the CT-simulation position and after setup for fractionated stereotactic treatment. The simulation and treatment images are aligned through an initial registration using several feature points followed by a refined automatic matching process using an iterative-closest-point mapping-align algorithm. All of the video-surface images could be automatically transformed to the machine coordinate according to the calibration file obtained from a template image. Phantom tests have demonstrated that we can capture surface images of patients in a second with spatial resolution of sub-millimeter. A millimeter shift and one-degree rotation relative to the treatment machine can be accurately detected. The entire process takes about two minutes. Our primary result on patients involved in a clinical trial is very promising. This research is partially supported by INH Grant 1R43CA91690-01 and NIH CA88843.

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Automatic detection of head refixation errors in fractionated stereotactic radiotherapy (FSR)

Abstract

Publication series

Other

ASJC Scopus subject areas

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