医疗隐私保护：GHM与Canny边缘检测驱动的信息隐藏技术

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本文主要探讨了"基于GHM和Canny边缘检测的医疗隐私保护信息隐藏"这一研究领域。作者Ren Shuai、Zhao Xiangmo和Zhang Tao来自西安长安大学的信息工程学院和电子与控制工程学院，他们于2014年8月25日接收了这篇论文，并在同年11月进行了修订和接受。该研究成果发表于2015年的《应用数学与信息科学》(Applied Mathematics & Information Sciences)期刊，卷9，第3期，页码1587-1592。文章的核心目标是为了保护患者的个人和诊断信息，利用全局哈密顿滤波器(GHM，Global Hamiltonian Method)和Canny边缘检测技术对原始的CT数字图像进行处理。GHM首先对图像进行全局分析，通过多小波分解，将CT图像划分成四个不同重要性的层次：LL2（重要性最高）、LH2、HL2和HH2（重要性最低）。这样做的目的是确保敏感信息被适当地隔离和区分。接着，算法对这些分布的子图像应用Canny边缘检测。在实际操作中，对于LL2和HH2这两个重要程度明显的层次，采用强度较高的Canny方法来检测边缘。然而，Canny边缘检测通常会识别出许多细小的边缘，这些边缘对于医学诊断可能是无关的，但包含了潜在的隐私信息。关键步骤在于，通过删除和比较这些无效或不相关的边缘，研究人员能够有效地隐藏隐私和诊断数据。实验结果显示，这种方法显著提高了水印CT图像的鲁棒性和信息隐藏容量，即在保持图像质量的同时，能够安全地隐藏更多的秘密信息，从而保护患者的隐私。这项研究为医疗图像的隐私保护提供了一种创新且有效的策略，利用GHM的全局分析和Canny边缘检测技术实现了对敏感信息的精细控制和隐藏，有助于在满足医疗需求的同时，确保患者数据的安全。这在当前大数据和信息安全日益重要的背景下具有重要意义。

Appl. Math. Inf. Sci. 9, No. 3, 1587-1592 (2015) 1587

Applied Mathematics & Information Sciences

An International Journal

http://dx.doi.org/10.12785/amis/090355

Information Hiding for Medical Privacy Protection based

on GHM and Canny Edge Detection

Ren Shuai

1,∗

, Zhao Xiangmo

and Zhang Tao

School of Information Engineering, Chang’an University, Xi’an 710064, China

School of Electronic and Control Engineering, Chang’an University, Xi’an 710064, China

Received: 25 Aug. 2014, Revised: 25 Nov. 2014, Accepted: 26 Nov. 2014

Published online: 1 May 2015

Abstract: In order to protect the personal and diagnosis information of patient, GHM and Canny edge detection are employed in this

algorithm to process the original CT digital image. The original image will be ﬁrstly processed GHM for a global analysis. According

to different importance degrees, CT images can be distributed into LL

, LH

, HL

and HH

by GHM multi-wavelet. After that, the

distributed sub-images will be processed by Canny edge detection. For example, the edges of LL

(with the highest important degree)

and HH

(with the lowest important degree) are detected by strong Canny method. Then many thin edges can be obtained, which are

useless for medical diagnosis, privacy and diagnosis information can be hid by deletion and comparison processing of invalid edges.

The experimental results indicate that the robustness and capacity of watermarked CT images can be improved after this algorithm.

Keywords: Diagnosis Gray or Binary Image, Privacy Protection, GHM Multi-Wavelet, Canny Edge Detection.

1 Introduction

Nowadays, personal privacy security has become one of

the issues concerned most in digital era. Long after

sectors like banking and ﬁnance, recently more and more

digital auxiliary diagnostic equipment are brought into

daily practical operation in medicine ﬁeld. Individual

medical records, carrying ever more sensitive personal

information, are already being gathered and stored by the

tens of thousands in databanks maintained by hospital

networks, health maintenance organizations, and drug

companies [

1]. As a result, information storage methods

of the patients have changed from papery-based into

electronic-based.

There are several common image formats in medical

ﬁeld, such as CT, MRI, X-ray, and so on. Some of those

electronic-based images are in analog formats and others

are in digital formats. Because of the convenience of the

digital images, the old analog images are converted into

digital ones. One of the problems brought by the popular

of digital medical images is the privacy information

security, which will make the relationship between both

sides of the health care worse. And reasonable method

can solve the problem. It is well known that digital

products can easily be illegally edited, modiﬁed, copied

and disseminated. These properties bring great

convenience, but at the same time it will inevitably

produce the issue of privacy disclosure of patients

information. Considering about the medical

characteristics, some scholars use the professional

mathematical model to analyze the natural system images

of human body [

2]. This model can simplify the

representation of some special medical images, like MRI

brain image, so it can ﬁnd some redundancy to be the

storage space. Refer to it, getting the redundancy of

medical images will be the ﬁrst concern of our algorithm,

but the algorithm proposed in our research can be used to

handle many kinds of medical images, rather than limited

to MRI images. Many other scholars achieve the goals of

medical privacy protection and authentication by using

watermarking [

3]. Most of these schemes embed robust

watermark into the digital medical images based on

frequency-domain methods, such as DCT, DWT, DFT,

and so on. And almost all of them select the appropriate

coefﬁcients for watermark embedding [

4].

Most of the digital medical images are gray scale

images, and some of them are the binary images. Based

on our previous studies, we know very well about the

properties of gray scale and binary images [

5]. From [6]

we ﬁnd that GHM multi-wavelet transform has much

∗

Corresponding author e-mail:

maxwellren@qq.com

 2015 NSP

Natural Sciences Publishing Cor.

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