Adaptive Wiener filter based on Gaussian mixture model for denoising chest X-ray CT image

Proceedings of the SICE Annual Conference

Volumn , Issue , 2007, Pages 682-689

  Tabuchi, Motohiro ^a   Yamane, Nobumoto ^a   Morikawa, Yoshitaka ^a  

^a OKAYAMA UNIVERSITY   (Japan)

Author keywords

Adaptive wiener filter; Expectation maximization algorithm; Gaussian mixture distribution model; Maximum a posteriori probability; Phantom

Indexed keywords

ADAPTIVE FILTERING; COMPUTERIZED TOMOGRAPHY; HEALTH; IMAGE ENHANCEMENT; IMAGING TECHNIQUES; MAGNETOSTRICTIVE DEVICES; PHOTODEGRADATION; TRELLIS CODES; WAVE FILTERS; WHITE NOISE;

ADAPTIVE WIENER FILTER; ADAPTIVE WIENER FILTERING; ANNUAL CONFERENCE; CONTROL ENGINEERS; CT IMAGING; DE-NOISING; DIAGNOSTIC IMAGING; EXPECTATION-MAXIMIZATION ALGORITHM; GAUSSIAN MIXTURE DISTRIBUTION MODEL; GAUSSIAN MIXTURE DISTRIBUTIONS; GAUSSIAN MIXTURE MODEL; GAUSSIAN WHITE-NOISE; HIGH-DOSE; HIGH-SPATIAL RESOLUTION; IMAGE SETS; LOW-DOSE; MAXIMUM A POSTERIORI PROBABILITY; PHANTOM; SIMULATION RESULTS; SLICE IMAGING; X-RAY CT;

ELECTRIC INSTRUMENT TRANSFORMERS;

EID: 50249153697     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/SICE.2007.4421069     Document Type: Conference Paper

References (12)

1. Jiang Hsieh: Adaptive streak artifact reduction in computed tomography resulting from excessive x-ray photon noise. American Association of Physicists in Medicine, vol.25, no.11, 2139-2147, (1998).
2. Marc Kachelrieβ, Oliver Watzke and Willi A.Kalender: Generalized multi-dimensional adaptive filtering for conventional and spiral single-slice, and cone-beam CT. American Association of Physicists in Medicine, vol.28, no.4, 475-490, (2001).
3. Issei Mori, Masahiro Kazama: Method for Suppressing Streak Artifacts in CT Resulting from Excessive NOise. Med Imag Tech,vol.21,no.4, 272-276, (2003).
4. Miwa Okumura, Takamasa Ota, and Shunsuke Tsukagoshi, et al.: New Method of Evaluating Edge-preserving Adaptive Filters for Computed Tomography(CT) : Digital Phantom Method. Jpn J Radiol Technol, vol.62, no.7, 971-978, (2006).
5. Naruomi Yasuda, Yoko Ishikawa and Yoshie Kodera: Improvement of Image Quality in chest MDCT Using Nonlinear Wavelet Shrinkage with Trimmed-thresholding. Jpn J Radiol Technol, vol.61, no.12, 1599-1608, (2005).
6. Yoshinori Funama, Yoshio Noguchi, Masamichi Shimamura: Reduction of Artifacts in Degraded CT Image by Adaptive Wiener Filter. Transactions of the Japanese Society for Medical and Biological Engineering, vol.40, no.1 (2002).
7. Masao Nakagawa,Toshiaki Makabe: Stochastic Processes, pp. 163-173, Baifukan CO.LTD,Tokyo, (2002).
8. P.A.Maragos,R.W.Shafer and R.M. Mersereau: Two-Dimensional Linear Prediction and Its Apprication to Adaptive Predictive Coding of Images. IEEE Trans, vol. ASSP -32, no.6, 1213-1228, (1998).
9. S.Mallat, G.Paranicolaou and Z.Zhang: Adaptive Covariance estimation of Locally Stationary Processes. Ann. Statistics, vol.26, no.1 1-47, (1998).
10. Nobumoto Yamane, Yoshitaka Morikawa, Yoichi Kawakami and Hidekazu Takahashi: An Optimal Noise Removal Using Adaptive Wiener Filter Based on Locally Stationary Gaussian Mixture Distribution Model for Images. Institute of Electronics Information and Communication Engineers of Japan, vol.J85-A, no.9, 993-1004, (2002).
11. Jinfang Wang, Masaaki Taguri, Shu Teduka and etal.: calculation of statistics I, New technique of the probability calculation, frontier of statistics science 11, pp.157-163, Iwanami Shoten,Tokyo,(2003).
12. Hiroki Nakano,Shizuo Yamamoto,Yasuo Yoshida: Signal processing and Image processing by Wavelet transform, pp, 144-149,Kyoritsu-Shuppan CO.LTD.,Tokyo,(1999).