Planar Scintigraphic Images Denoising

Planar Scintigraphic Images Denoising

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 natu...

Comparaison de techniques de débruitage des images scintigraphiques Comparison of denoising techniques of scintigraphic images

Scintigraphic images are strongly affected by Poisson noise. This article presents the results of a comparison between denoising methods for Poisson noise according to different criteria: the gain in signal-to-noise ratio, the preservation of resolution and contrast, and the visual quality. The wavelet techniques recently developed to denoise Poisson noise limited images are divided into two gr...

An Efficient Curvelet Framework for Denoising Images

Wiener filter suppresses noise efficiently. However, it makes the out image blurred. Curvelet preserves the edges of natural images perfectly, but, it produces visual distortion artifacts and fuzzy edges to the restored image, especially in homogeneous regions of images. In this paper, a new image denoising framework based on Curvelet transform and wiener filter is proposed, which can stop nois...

Improved lesion detection from spatially adaptive, minimally complex, Pixon reconstruction of planar scintigraphic images.

Pixon noise reduction was applied to 18 planar images, six each from 99mTc-methylene diphosphonate (99mTc-MDP), 67Ga citrate (67Ga), and (123)I-metaiodobenzylguanidine ((123)I-MIBG) studies. Pixon processing increased patient signal-to-noise ratio, 6.8-11.8 fold. Three specialists preferred processed images 44 of 54 times with good agreement (87%). Most (9/10, p<0.02) of the null and negative p...

Denoising of Fingerprint Images