A multiscale contrast enhancement algorithm for breast cancer detection using Laplacian Pyramid

Xiaoming Liu, J. Tang, Si Xiong, Zhilin Feng, Zhaohui Wang
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引用次数: 20

Abstract

Mammography is currently regarded as one of the best ways to detect breast cancer in the early stage. However, due to the limitation in imaging condition and the subtleness of the difference between normal and abnormal features, it is generally difficult to interpret the mammograms. Thus, image enhancement techniques have been widely used in screening mammograms. In this paper, a multiscale contrast enhancement algorithm based on Laplacian Pyramid is developed to enhance the contrast of the mammograms and improve the discernibility of the abnormal features. In the proposed algorithm, an image is first decomposed into a multi-level Laplacian Pyramid and then the enhancement is performed in the reconstruction stage. A multiscale contrast measure is used to modify the coefficients iteratively level by level and the enhanced image is obtained at the lowest level. Experiments proved the effectiveness of the proposed algorithm.
基于拉普拉斯金字塔的乳腺癌检测多尺度对比度增强算法
乳房x光检查目前被认为是早期发现乳腺癌的最佳方法之一。然而,由于影像学条件的限制和正常与异常特征之间的微妙差异,通常很难解释乳房x光片。因此,图像增强技术已广泛应用于乳房x光检查。本文提出了一种基于拉普拉斯金字塔的多尺度对比度增强算法,以增强乳房x光片的对比度,提高异常特征的可辨别性。该算法首先将图像分解为多层次的拉普拉斯金字塔,然后在重建阶段进行增强。采用一种多尺度对比度方法逐级迭代修改系数,在最低水平得到增强图像。实验证明了该算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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