Literature DB >> 12539975

Statistical and heuristic image noise extraction (SHINE): a new method for processing Poisson noise in scintigraphic images.

Pascal Hannequin1, Jacky Mas.   

Abstract

Poisson noise is one of the factors degrading scintigraphic images, especially at low count level, due to the statistical nature of photon detection. We have developed an original procedure, named statistical and heuristic image noise extraction (SHINE), to reduce the Poisson noise contained in the scintigraphic images, preserving the resolution, the contrast and the texture. The SHINE procedure consists in dividing the image into 4 x 4 blocks and performing a correspondence analysis on these blocks. Each block is then reconstructed using its own significant factors which are selected using an original statistical variance test. The SHINE procedure has been validated using a line numerical phantom and a hot spots and cold spots real phantom. The reference images are the noise-free simulated images for the numerical phantom and an extremely high counts image for the real phantom. The SHINE procedure has then been applied to the Jaszczak phantom and clinical data including planar bone scintigraphy, planar Sestamibi scintigraphy and Tl-201 myocardial SPECT. The SHINE procedure reduces the mean normalized error between the noisy images and the corresponding reference images. This reduction is constant and does not change with the count level. The SNR in a SHINE processed image is close to that of the corresponding raw image with twice the number of counts. The visual results with the Jaszczak phantom SPECT have shown that SHINE preserves the contrast and the resolution of the slices well. Clinical examples have shown no visual difference between the SHINE images and the corresponding raw images obtained with twice the acquisition duration. SHINE is an entirely automatic procedure which enables halving the acquisition time or the injected dose in scintigraphic acquisitions. It can be applied to all scintigraphic images, including PET data, and to all low-count photon images.

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Year:  2002        PMID: 12539975     DOI: 10.1088/0031-9155/47/24/302

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  3 in total

1.  Properties of noise in positron emission tomography images reconstructed with filtered-backprojection and row-action maximum likelihood algorithm.

Authors:  A Teymurazyan; T Riauka; H-S Jans; D Robinson
Journal:  J Digit Imaging       Date:  2013-06       Impact factor: 4.056

2.  Adaptive noise reduction of scintigrams with a wavelet transform.

Authors:  Koichi Ogawa; Masahiko Sakata; Yu Li
Journal:  Int J Biomed Imaging       Date:  2012-02-28

3.  A based bayesian wavelet thresholding method to enhance nuclear imaging.

Authors:  Nawrès Khlifa; Najla Gribaa; Imen Mbazaa; Kamel Hamruoni
Journal:  Int J Biomed Imaging       Date:  2009-03-26
  3 in total

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