Statistical Characterization of Portal Images and Noise from Portal Imaging Systems

In this paper, we consider the statistical characteristics of the so-called portal images, which are acquired prior to the radiotherapy treatment, as well as the noise that present the portal imaging systems, in order to analyze whether the well-known noise and image features in other image modalities, such as natural image, can be found in the portal imaging modality. The study is carried out in the spatial image domain, in the Fourier domain, and finally in the wavelet domain. The probability density of the noise in the spatial image domain, the power spectral densities of the image and noise, and the marginal, joint, and conditional statistical distributions of the wavelet coefficients are estimated. Moreover, the statistical dependencies between noise and signal are investigated. The obtained results are compared with practical and useful references, like the characteristics of the natural image and the white noise. Finally, we discuss the implication of the results obtained in several noise reduction methods that operate in the wavelet domain.

[1]  Edward H. Adelson,et al.  Noise removal via Bayesian wavelet coring , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[2]  L. Antonuk.  Electronic portal imaging devices: a review and historical perspective of contemporary technologies and research. , 2002, Physics in medicine and biology.

[3]  D J Field,et al.  Relations between the statistics of natural images and the response properties of cortical cells. , 1987, Journal of the Optical Society of America. A, Optics and image science.

[4]  M. L. Dewal,et al.  Efficient Denoising Technique for CT images to Enhance Brain Hemorrhage Segmentation , 2012, Journal of Digital Imaging.

[5]  Antonio Torralba,et al.  Statistics of natural image categories , 2003, Network.

[6]  C. Stein.  Estimation of the Mean of a Multivariate Normal Distribution , 1981 .

[7]  William Bialek,et al.  Statistics of Natural Images: Scaling in the Woods , 1993, NIPS.

[8]  L D Cromwell,et al.  Filtering noise from images with wavelet transforms , 1991, Magnetic resonance in medicine.

[9]  Thierry Blu,et al.  The SURE-LET Approach to Image Denoising , 2007, IEEE Transactions on Image Processing.

[10]  Thierry Blu,et al.  Multiframe sure-let denoising of timelapse fluorescence microscopy images , 2008, 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[11]  P. Munro,et al.  Clinical use of electronic portal imaging: report of AAPM Radiation Therapy Committee Task Group 58. , 2001, Medical physics.

[12]  Martin J Butson,et al.  Multilayer Gafchromic film detectors for breast skin dose determination in vivo. , 2002, Physics in medicine and biology.

[13]  I. Johnstone,et al.  Ideal spatial adaptation by wavelet shrinkage , 1994 .

[14]  Michael Unser,et al.  Wavelets in Medical Imaging , 2003, IEEE Trans. Medical Imaging.

[15]  Levent Sendur,et al.  A bivariate shrinkage function for wavelet-based denoising , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[16]  Ricardo José Ferrari,et al.  Digital Radiographic Image Denoising Via Wavelet-Based Hidden Markov Model Estimation , 2004, Journal of Digital Imaging.

[17]  M. Herman.  Clinical use of electronic portal imaging. , 2005, Seminars in radiation oncology.

[18]  I. Johnstone,et al.  Adapting to Unknown Smoothness via Wavelet Shrinkage , 1995 .

[19]  Eero P. Simoncelli,et al.  Natural image statistics and neural representation. , 2001, Annual review of neuroscience.

[20]  Alan V. Oppenheim,et al.  Discrete-time signal processing (2nd ed.) , 1999 .

[21]  Thierry Blu,et al.  A New SURE Approach to Image Denoising: Interscale Orthonormal Wavelet Thresholding , 2007, IEEE Transactions on Image Processing.

[22]  Jorge Larrey-Ruiz,et al.  SURE-LET and BLS-GSM wavelet-based denoising algorithms versus linear Local Wiener Estimator in Radiotherapy portal image denoising. , 2009 .

[23]  Michael Unser,et al.  SPECIAL ISSUE ON WAVELETS IN MEDICAL IMAGING , 2003 .

[24]  Martin J. Wainwright,et al.  Image denoising using scale mixtures of Gaussians in the wavelet domain , 2003, IEEE Trans. Image Process..

[25]  Eero P. Simoncelli,et al.  Random Cascades on Wavelet Trees and Their Use in Analyzing and Modeling Natural Images , 2001 .