Dr. Shidong Li Profile

Dr. Shidong Li

Assistant Professor of Radiation Oncology at Temple Univ Hospital

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Publications (3)

Proceedings Article | 8 March 2013 Paper

Automatic respiration tracking for radiotherapy using optical 3D camera

Tuotuo Li, Jason Geng, Shidong Li

Proceedings Volume 8618, 861804 (2013) https://doi.org/10.1117/12.2003202

KEYWORDS: 3D image processing, Principal component analysis, Radiotherapy, Automatic tracking, Imaging systems, Motion analysis, 3D acquisition, Cameras, Radio optics, Stereoscopic cameras

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Rapid optical three-dimensional (O3D) imaging systems provide accurate digitized 3D surface data in real-time, with no patient contact nor radiation. The accurate 3D surface images offer crucial information in image-guided radiation therapy (IGRT) treatments for accurate patient repositioning and respiration management. However, applications of O3D imaging techniques to image-guided radiotherapy have been clinically challenged by body deformation, pathological and anatomical variations among individual patients, extremely high dimensionality of the 3D surface data, and irregular respiration motion. In existing clinical radiation therapy (RT) procedures target displacements are caused by (1) inter-fractional anatomy changes due to weight, swell, food/water intake; (2) intra-fractional variations from anatomy changes within any treatment session due to voluntary/involuntary physiologic processes (e.g. respiration, muscle relaxation); (3) patient setup misalignment in daily reposition due to user errors; and (4) changes of marker or positioning device, etc. Presently, viable solution is lacking for in-vivo tracking of target motion and anatomy changes during the beam-on time without exposing patient with additional ionized radiation or high magnet field. Current O3D-guided radiotherapy systems relay on selected points or areas in the 3D surface to track surface motion. The configuration of the marks or areas may change with time that makes it inconsistent in quantifying and interpreting the respiration patterns. To meet the challenge of performing real-time respiration tracking using O3D imaging technology in IGRT, we propose a new approach to automatic respiration motion analysis based on linear dimensionality reduction technique based on PCA (principle component analysis). Optical 3D image sequence is decomposed with principle component analysis into a limited number of independent (orthogonal) motion patterns (a low dimension eigen-space span by eigen-vectors). New images can be accurately represented as weighted summation of those eigen-vectors, which can be easily discriminated with a trained classifier. We developed algorithms, software and integrated with an O3D imaging system to perform the respiration tracking automatically. The resulting respiration tracking system requires no human intervene during it tracking operation. Experimental results show that our approach to respiration tracking is more accurate and robust than the methods using manual selected markers, even in the presence of incomplete imaging data.

Proceedings Article | 8 March 2013 Paper

Medical applications of fast 3D cameras in real-time image-guided radiotherapy (IGRT) of cancer

Shidong Li, Tuotuo Li, Jason Geng

Proceedings Volume 8618, 861802 (2013) https://doi.org/10.1117/12.2002603

KEYWORDS: Stereoscopic cameras, Imaging systems, Radiotherapy, Cameras, Video, Principal component analysis, Lung, Tumors, X-ray computed tomography, Computed tomography

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Proceedings Article | 8 March 2013 Paper

Performance assessment of 3D surface imaging technique for medical imaging applications

Tuotuo Li, Jason Geng, Shidong Li

Proceedings Volume 8618, 861803 (2013) https://doi.org/10.1117/12.2001456

KEYWORDS: 3D image processing, Cameras, Imaging systems, 3D acquisition, Stereoscopy, Calibration, 3D modeling, Stereoscopic cameras, Projection systems, Radiotherapy

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