灰度变换下多模态刚性医学图像分层增强仿真
Simulation of Multi-Modal Rigid Medical Image Layered Enhancement under Grayscale Transformation
徐立 1刘亮 1赵凤军2
作者信息
- 1. 内蒙古科技大学包头医学院,内蒙古 包头 014040
- 2. 西北大学信息科学与技术学院,陕西 西安 710127
- 折叠
摘要
为了提升医学图像增强效果,有效保留图像细节,提出基于灰度变换的多模态刚性医学图像增强算法.对多模态刚性医学图像去噪处理,采用免疫优化算法对自适应阈值优化处理,选择最佳阈值.根据去噪结果通过小波变换将医学图像分解为多个不同区间,分别对各个区间实行灰度变换处理,根据变换后的结果获取分层增强效果,实现多模态刚性医学图像的整体增强.经实验测试结果表明,所提算法可以获取更加满意的医学图像增强效果,提高了图像清晰度,图像视觉效果显著增强.
Abstract
In order to improve the medical image enhancement and preserve the image in details,this paper pres-ented a multi-modal rigid medical image enhancement algorithm based on grayscale transformation.Firstly,the noise was removed from multi-modal rigid medical image,and the immune algorithm was adopted to optimize the adaptive threshold and thus to select the best threshold.Based on the denoising result,the medical images were divided into different intervals by wavelet transformation,and then the grayscale transformation was performed on each interval.Af-ter that,the layered enhancement effect was obtained.Finally,the overall enhancement of multi-modal rigid medical image was achieved.The experimental results show that the proposed algorithm can obtain a more ideal enhancement effect of medical image,and improves the clarity,and enhances the visual effect significantly.
关键词
灰度变换/图像增强/图像去噪/免疫优化算法/小波变换Key words
Grayscale transformation/Image enhancement/Image denoising/Immune optimization algorithm/Wavelet transform引用本文复制引用
基金项目
内蒙古自治区自然科学基金(2019MS06036)
内蒙古自治区卫生健康科技计划(202201399)
包头医学院花蕾计划(2020)(HL202018)
出版年
2024
NETL
NSTL
万方数据