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

Recent development in optical 3D surface imaging technologies provide better ways to digitalize the 3D surface and its motion in real-time. The non-invasive 3D surface imaging approach has great potential for many medical imaging applications, such as motion monitoring of radiotherapy, pre/post evaluation of plastic surgery and dermatology, to name a few. Various commercial 3D surface imaging systems have appeared on the market with different dimension, speed and accuracy. For clinical applications, the accuracy, reproducibility and robustness across the widely heterogeneous skin color, tone, texture, shape properties, and ambient lighting is very crucial. Till now, a systematic approach for evaluating the performance of different 3D surface imaging systems still yet exist. In this paper, we present a systematic performance assessment approach to 3D surface imaging system assessment for medical applications. We use this assessment approach to exam a new real-time surface imaging system we developed, dubbed "Neo3D Camera", for image-guided radiotherapy (IGRT). The assessments include accuracy, field of view, coverage, repeatability, speed and sensitivity to environment, texture and color.

[1]  Minsong Cao Image-guided Stereotactic Body Radiation Therapy , 2011 .

[2]  David Djajaputra,et al.  Real-time 3D surface-image-guided beam setup in radiotherapy of breast cancer. , 2004, Medical physics.

[3]  Roger Y. Tsai,et al.  A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses , 1987, IEEE J. Robotics Autom..

[4]  Steven Yi,et al.  3D FaceCam: a fast and accurate 3D facial imaging device for biometrics applications , 2004, SPIE Defense + Commercial Sensing.

[5]  Benjamin Movsas,et al.  A technique of quantitatively monitoring both respiratory and nonrespiratory motion in patients using external body markers. , 2007, Medical physics.

[6]  Jason Geng,et al.  DLP-based structured light 3D imaging technologies and applications , 2011, MOEMS-MEMS.

[7]  J F Dicello,et al.  A simple and accurate coordinate transformation for a stereotactic radiotherapy system. , 1999, Medical physics.

[8]  C. Pelizzari,et al.  Unfolding patient motion with biplane radiographs. , 1994, Medical physics.

[9]  J. Buatti,et al.  The University of Florida frameless high-precision stereotactic radiotherapy system. , 1997, International journal of radiation oncology, biology, physics.

[10]  G T Chen,et al.  Correlation of projection radiographs in radiation therapy using open curve segments and points. , 1992, Medical physics.

[11]  Lei Xing,et al.  Image-Guided and Adaptive Radiation Therapy , 2012 .

[12]  Zhengyou Zhang,et al.  A Flexible New Technique for Camera Calibration , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  Jason Geng,et al.  Automatic respiration tracking for radiotherapy using optical 3D camera , 2013, Photonics West - Micro and Nano Fabricated Electromechanical and Optical Components.

[14]  W Schlegel,et al.  Photogrammetric accuracy measurements of head holder systems used for fractionated radiotherapy. , 1994, International journal of radiation oncology, biology, physics.

[15]  J. Geng Volumetric 3D Display for Radiation Therapy Planning , 2008, Journal of Display Technology.

[16]  Jason Geng,et al.  Structured-light 3D surface imaging: a tutorial , 2011 .

[17]  Hamid Dehghani,et al.  Breast deformation modelling for image reconstruction in near infrared optical tomography. , 2004, Physics in medicine and biology.

[18]  B. Movsas,et al.  Dose delivered from Varian's CBCT to patients receiving IMRT for prostate cancer , 2007, Physics in medicine and biology.

[19]  George T. Y. Chen,et al.  A phantom evaluation of a stereo-vision surface imaging system for radiotherapy patient setup. , 2005, Medical physics.

[20]  Dezhi Liu,et al.  Automatic detection of head refixation errors in fractionated stereotactic radiotherapy (FSR) , 2004, 2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro (IEEE Cat No. 04EX821).