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A Novel Variation on Non Local Means Algorithm for Denoising of Contrast-Enhanced MR Images

X. Ignatius Selvarani

Abstract


Dynamic Contrast-enhanced magnetic resonance Imaging yields information about the Hemodynamic, properties of tissues and extracellular leakage space. The task is further complicated by the presence of hardware-induced noise, geometric distortions, and intensity non-uniformities (bias field), as well as motion artifacts resulting from patient movement during image acquisition.  This paper presents a new algorithm for denoising dynamic contrast-enhanced (DCE) MR images, called dynamic nonlocal means. It is a variation of the nonlocal means (NLM) algorithm. DNLM exploits the redundancy of information in the temporal sequence of images. We also perform the qualitative and quantitative results which suggest that the DNLM algorithm is more effective in attenuating noise ria � a ��U�oHhow that histogram quadratic distance measure produced more accurate results for image retrieval as compared to other distance measures.

 

liedE � ht��U�oH) convolutional codes and compared with the (2,1,7) convolutional codes. The proposed interleaver is applied to different bits stream lengths of 1024, 2048, 4096, 8192, and 16384 bits. The simulation results show the superiority of the proposed chaotic interleaved convolutional codes scheme over the traditional schemes in the image transmission over the mobile channels with respect the shorter constraint length of the encoder. Also, the chaotic interleaver performs better with the packet length increasing. The chaotic interleaver enhances the security with the different secret key for every transmitted packet. The computer simulations are carried out using the widely accepted Jakes’ model. The results reveal that the proposed scenarios can be applied to the long bit stream packets technologies such as Wimax.

 


Keywords


Denoising, Dynamic Contrast-Enhanced (DCE) Magnetic Resonance Imaging (MRI), Dynamic Nonlocal Means (DNLM), Noise, Nonlocal Means.

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