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A comparative study of MRI contrast enhancement techniques based on Traditional Gamma Correction and Adaptive Gamma Correction: Case of multiple sclerosis pathology

机译:基于传统γ校正和自适应γ校正的MRI对比增强技术的对比研究:多发性硬化病理学的情况

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One of the most important preprocessing techniques is image Contrast Enhancement which is a technique that improve visual quality of an input image becoming more suitable for human analysis and perception. Numerous researches have been already developed for enhancement of Medical image for their important application, Traditional Gamma Correction is found to be one of the simplest technique for the contrast enhancement of medical image. This technique uses a set of varying parameter (y, c) which adjust effectively gray value intensity of the input image. Otherwise, Adaptive Gamma Correction technique have been appeared and have been proved its effectiveness by the use of adaptive (y, c) parameter which are determined adaptively from statistical information of input image. Traditional Gamma Correction (TGC) and Adaptive Gamma Correction (AGC) have been applied on three brain MRI modalities for patient with Multiple Sclerosis pathology. Qualitative and quantitative results are presented to illustrate the comparison of TGC and AGC to enhance the contrast of MRI images for better appearance of normal tissue and diseased tissue affected by MS pathology.
机译:最重要的预处理技术之一是图像对比度增强,其是提高输入图像的视觉质量的技术变得更适合人类分析和感知。已经开发了许多研究,用于增强医学形象的重要应用,发现传统的伽马校正是医学图像对比增强的最简单技术之一。该技术使用一组不同参数(y,c),其调整输入图像的有效灰度值强度。否则,已经出现了自适应(y,c)参数已经出现了自适应(y,c)参数的有效性,该否则已经从输入图像的统计信息确定的自适应(y,c)参数证明了其有效性。传统的伽玛矫正(TGC)和适应性γ校正(AGC)已应用于具有多发性硬化病理学的患者的三种脑MRI方式。提出了定性和定量结果以说明TGC和AGC的比较,以增强MRI图像的对比度,以便更好地出现受MS病理学影响的正常组织和患病组织。

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