基于小波的图像增强算法在乳腺癌检测中的研究与应用

乳腺癌是现代女性最常见的恶性肿瘤之一,X光照片是一种在乳腺癌普查中广泛采用的检测手段。由于医学影像噪声大不清晰,检测结果往往不尽人意。本文以数字乳房X片图像为对象,研究了提高微钙化点的对比度的基于小波变换的图像增强算法。小波变换在时频域的多分辨率具有良好的空间域和频率域局部化特性。实验证明,基于小波多分辨率分析在抑制噪声的同时能对图像进行有效增强,提高图像的对比度,使钙化点的显示更为明显,提高了图像中病灶重要特征的可视化。基于小波的图像去噪和增强算法作为医学诊断的辅助手段有极其重要的意义。

Research of Wavelet-based Image Enhancement Algorithm in Breast Cancer Diagnosis

Breast cancer is one of the most common malignant tumor of modern women.X-ray screening is widely used in breast cancer early detection.As medical image noise is not so clear,the test results are often unsatisfactory.This paper used X-ray breast digital images to improve the contrast of micro-calcifications by wavelet-based image enhancement algorithm.Wavelet transform has good spatial and frequency domain localization property in multi-resolution of time-frequency domain.Experimental results show that wavelet-based multi-resolution analysis not only suppressed the noise effectively,but also enhanced the image and improved image contrast,which making the calcification more visible and raising the important features of the image in the visualization of lesions.Wavelet-based image denoising and enhancement algorithms as an aid to medical diagnosis are extremely important.