改进颜色融合的医学图像彩色化技术

摘要

Coloring grey-level images has the advantage of highlighting the suspected regions,which helps with the communi-cation between doctors and patients.This paper proposed a new medical image colorization approach via an improved color fu-sion scheme.Firstly,it used KNN-based foreground/background segmentation to strengthen the outline.Secondly,it annotated the image with only a few user specified color scribbles.Finally,it introduced a color fusion algorithm to obtain a better color appearance for the medical image.The resulting image preserved the chromatic information of the source image and retained the original luminance of the colored image.In experiments,the algorithm has a high accuracy and the results demonstrate a good potential for practical applications of the proposed algorithm in the medical image processing.%彩色化后的医学图像能清晰体现患者病灶信息有利于医患沟通。提出改进颜色融合的医学图像彩色化方法，首先利用基于KN N的图像前背景区分算法，强化病灶区域的边界信息；然后以此为约束条件，只需提供简单的着色输入；最后将边界能量引入颜色融合方法，得到较好的着色结果。着色图像保持了原图的灰度信息不变，增加了彩色标记图像的颜色和真实感。实验结果表明，该算法具有较高的精确度，可有效地应用于医学图像彩色化处理。