Literature DB >> 20426132

Correlating chest surface motion to motion of the liver using epsilon-SVR--a porcine study.

Floris Ernst1, Volker Martens, Stefan Schlichting, Armin Besirević, Markus Kleemann, Christoph Koch, Dirk Petersen, Achim Schweikard.   

Abstract

In robotic radiosurgery, the compensation of motion of internal organs is vital. This is currently done in two phases: an external surrogate signal (usually active optical markers placed on the patient's chest) is recorded and subsequently correlated to an internal motion signal obtained using stereoscopic X-ray imaging. This internal signal is sampled very infrequently to minimise the patient's exposure to radiation. We have investigated the correlation of the external signal to the motion of the liver in a porcine study using epsilon-support vector regression. IR LEDs were placed on the swines' chest. Gold fiducials were placed in the swines' livers and were recorded using a two-plane X-ray system. The results show that a very good correlation model can be built using epsilon-SVR, in this test clearly outperforming traditional polynomial models by at least 45 and as much as 74%. Using multiple markers simultaneously can increase the new model's accuracy.

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Year:  2009        PMID: 20426132     DOI: 10.1007/978-3-642-04271-3_44

Source DB:  PubMed          Journal:  Med Image Comput Comput Assist Interv


  6 in total

1.  Fast and robust extraction of surrogate respiratory signal from intra-operative liver ultrasound images.

Authors:  Jiaze Wu; Cheng Li; Su Huang; Feng Liu; Bien Soo Tan; London Lucien Ooi; Haoyong Yu; Jimin Liu
Journal:  Int J Comput Assist Radiol Surg       Date:  2013-06-08       Impact factor: 2.924

2.  Correlation between external and internal respiratory motion: a validation study.

Authors:  Floris Ernst; Ralf Bruder; Alexander Schlaefer; Achim Schweikard
Journal:  Int J Comput Assist Radiol Surg       Date:  2011-08-19       Impact factor: 2.924

3.  Respiratory motion estimation of the liver with abdominal motion as a surrogate.

Authors:  Shamel Fahmi; Frank F J Simonis; Momen Abayazid
Journal:  Int J Med Robot       Date:  2018-08-15       Impact factor: 2.547

4.  Development of AI-driven prediction models to realize real-time tumor tracking during radiotherapy.

Authors:  Dejun Zhou; Mitsuhiro Nakamura; Nobutaka Mukumoto; Hiroaki Tanabe; Yusuke Iizuka; Michio Yoshimura; Masaki Kokubo; Yukinori Matsuo; Takashi Mizowaki
Journal:  Radiat Oncol       Date:  2022-02-23       Impact factor: 3.481

5.  Correlation of Optical Surface Respiratory Motion Signal and Internal Lung and Liver Tumor Motion: A Retrospective Single-Center Observational Study.

Authors:  Guangyu Wang; Xinyu Song; Guangjun Li; Lian Duan; Zhibin Li; Guyu Dai; Long Bai; Qing Xiao; Xiangbin Zhang; Ying Song; Sen Bai
Journal:  Technol Cancer Res Treat       Date:  2022 Jan-Dec

6.  Tracking lung tumors in orthogonal X-rays.

Authors:  Feng Li; Fatih Porikli
Journal:  Comput Math Methods Med       Date:  2013-08-06       Impact factor: 2.238

  6 in total

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