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Proceedings Paper

Performances of a specific denoising wavelet process for high-resolution gamma imaging
Author(s): Annie Pousse; Christophe Dornier; Michel Parmentier; Bruno Kastler; Jerome Chavanelle
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Paper Abstract

Due to its functional capabilities, gamma imaging is an interesting tool for medical diagnosis. Recent developments lead to improved intrinsic resolution. However this gain is impaired by the poor activity detected and the Poissonian feature of gamma ray emission. High resolution gamma images are grainy. This is a real nuisance for detecting cold nodules in an emitting organ. A specific translation wavelet filter which takes into account the Poissonian feature of noise, has been developed in order to improve the diagnostic capabilities of radioisotopic high resolution images. Monte Carlo simulations of a hot thyroid phantom in which cold spheres, 3-7 mm in diameter, could be included were performed. The loss of activity induced by cold nodules was determined on filtered images by using catchment basins determination. On the original images, only 5-7 mm cold spheres were clearly visible. On filtered images, 3 and 4 mm spheres were put in prominent. The limit of the developed filter is approximately the detection of 3 mm spherical cold nodule in acquisition and activity conditions which mimic a thyroid examination. Furthermore, no disturbing artifacts are generated. It is therefore a powerful tool for detecting small cold nodules in a gamma emitting medium.

Paper Details

Date Published: 27 February 2004
PDF: 12 pages
Proc. SPIE 5266, Wavelet Applications in Industrial Processing, (27 February 2004); doi: 10.1117/12.515940
Show Author Affiliations
Annie Pousse, Univ. de Franche-Comte (France)
Christophe Dornier, Hopitaux Universitaires de Geneve (Switzerland)
Michel Parmentier, Univ. de Franche-Comte (France)
Bruno Kastler, Univ. de Franche-Comte (France)
Jerome Chavanelle, Univ. de Franche-Comte (France)

Published in SPIE Proceedings Vol. 5266:
Wavelet Applications in Industrial Processing
Frederic Truchetet, Editor(s)

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