Planar Scintigraphic Images Denoising  

作　　者：Fatma Makhlouf Hatem Besbes Nawres Khalifa Chokri Ben Amar Basel Solaiman 

机构地区：[1]Department Image and Information Processing, Technopole Brest-Iroise, Bretagne, France [2]Higher Institute of Medical Technology of Tunis, University of Tunis El Manar, Tunis, Tunisia [3]Research Group on Intelligent Machines, University of Sfax, National Engineering School of Sfax, Sfax, Tunisia [4]Research Unit of Biophysics, Faculty of Medicine of Tunis, Tunis, Tunisia

出　　处：《Open Journal of Medical Imaging》2013年第4期116-124,共9页医学影像期刊（英文）

摘　　要：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.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.

关 键 词：Poisson-Noise SCINTIGRAPHY Acquisition Wavelet CONTOURLET CURVELET Ridgelet BANDELET 

分 类 号：R73[医药卫生—肿瘤]