TITLE:
Planar Scintigraphic Images Denoising
AUTHORS:
Fatma Makhlouf, Hatem Besbes, Nawres Khalifa, Chokri Ben Amar, Basel Solaiman
KEYWORDS:
Poisson-Noise; Scintigraphy; Acquisition; Wavelet; Contourlet; Curvelet; Ridgelet; Bandelet
JOURNAL NAME:
Open Journal of Medical Imaging,
Vol.3 No.4,
December
6,
2013
ABSTRACT: Scintigraphic images are generally affected by a Poisson type random
noise which diminishes qualitatively and quantitatively the
images. Restoration techniques aim to “find” an object from one (or several) degraded
observation(s). The objective of the restoration is then to produce an image
closer to the physical reality. So that the restoration is successful, it is
very useful to know the nature of degradation. In this work, we
present a planar scintigraphic acquisition chain modeling. This model takes
into account the Poisson noise and its stationarity aspect. Then, we present a
comparative study of the multi-resolution methods used to reduce the noise in
scintigraphic images. Scintigraphy is a tool for exploring
functionally several pathologies: the ventricular ejection fraction, the renal
clearance and the thyroid activity. Given the fact that scintigraphic images
are strongly affected by noise, the objective in this work is to enhance scintigraphic
images for a reliable diagnosis and better orientation and understanding of the
pathological phenomenon. This paper focuses on two main parts: the first
deals with the degradation of model while the second takes into consideration
the comparison of the multi-resolution methods for assessing the quality of
scintigraphic images to reduce noise using wavelet, contourlet, curvelet,
ridgelet and bandelet transformations.