区域对比度模糊增强及其在医学图象边界检测中的应用

本文在广义模糊集合与广义模糊算子的基础上,给出了一种基于增强图象区域之间对比度的边界检测算法,并利用升半梯形模糊分布将空间域的灰度图象变换为对应的广义隶属度函数。实验结果表明该算法对于灰度层次丰富的医学图象边界提取效果是较好的。     

线性的医学图像边界检测方法中六种算子的比较

图象的边界检测是图象处理的一个重要部分。本文根据实践经验首先提出了边界检测的评判标准，继而对几种线性算法进行了描述，并将它们用ＶｉｓｕａｌＢａｓｉｃ语言对同一图象进行了实现，从而直观地反映了各算法的优劣，为我们处理实际的医学图象提供了基础。     

医学图象灰度信息处理装置

作者根据图象信息处理理论,研制成一个能改变图象大小,实现图象反转,突出病灶边缘,改善图象反差以及对图象灰度进行相对半定量测定的医学图象灰度信息提取装置。该装置可用以提高医学图象的直接判读能力和诊断可靠性。     

利用二维匹配滤波器由视网膜图象检测血管

尽管目前许多文献提供了种类繁多的检测边界的运算规则,但这些检测边界的运算规则在一幅图象上通常得不到各种满意的特征结果。在这篇文章中,作者将提出由视网膜图象检测其血管的问题。由于血管的局部对比度通常比较弱,因此采用原有的边界检测运算规则将不能得到令人满意的结果。作者将根据要辨认部位的光学和立体特性引入一个提取特征的筛单运算因子,采用这种运算因子的运算方法保留了边界运算因子的边     

北京生物医学工程1997年索引

北京生物医学工程１９９７年索引主题索引（主题关键词以汉语拼音为序）Ｂ边界处理医学图象的边界处理（刘毅等）１９９７；１６（１）：１补体生物材料体外动态血清接触对ＣＨ５０及补体的影响（曾怡等）１９９７；１６（３）：１７２Ｃ超声超声检测血流速度的时域相关方...     

一种基于提取轮廓的医学图象数据压缩编码方法

本文提出了一种对医学图象进行轮廓编码和采用二维快速离散余弦变换（2D－FDCT）对其背景图象数据压缩编码相结合的方法。首先对2^t*2^t（t=9)，点的原始医学数字图象采用可变阈值的Sobel算子提出其边缘图象，原始图象与边缘图象之差为背景图象，利用5＊5点邻域窗函数对此背景图象2：1内抽成2t^-1*2^t-1点的数字图象，利用上述方法对此2t-1*2t-1点的数字图象进行分解……直到剩下64＊64点的背景图象，本文对几级轮廓图象采用等值线编码压缩，对64＊64点的背景图象通过采用快速多项式变换（FPT）计算2D－FDCT来进行数据压缩编码，在接收端，在接收端，对恢复的各级背景图象再叠加上相应的[边缘图象可减少重建图象产生的边缘模糊效应，我们在IBM－PC／XT微机组成的小型图象处理系统上进行了医学的编码压缩实验，图象数据压缩比可达20：1以上。     

一种基于人类感知的医学图象压缩方法

作者详细地介绍了一种基于人类感知的医学图象压缩算法，它利用人类视觉的运动特性，空间频率特性及时间频率特性对静止灰度图象进行有限失真压缩，该方法能大大压缩图象数据提高压缩比，对医学图象的压缩是一种比较有效的方法。     

医学图像中模糊边界的提取

本文提出了一种基于模糊数字拓扑的方法来实现医学图象中模糊对象的提取,该方法根据所给定的物体和边缘特征信息将原始医学图象转换到模糊连通空间,获得模糊边界,对复杂形状的对象还提出了模糊边界逐步改进和优化的算法,最终可以跟踪出满足实际需要的连通、平滑及优化的物体轮廓线,算法在超声图象中取得了满意的结果。     

心血管造影图像边缘特征的提取

心血管疾病作为老年人的常见病现在比较多见。根据血管造影图像，即时诊断、积极治疗，能预防病情的发展，解除患者的痛苦。对血管图像的边缘特征进行提取是求取血管直径、分析血管特征和构造心血管三维图像的基础。 提取血管造影图像中的纯血管图，提出利用圆模板灰度最小和微分边缘检测的方法。先利用圆模板灰度最小准则求取血管的路径，然后根据路径线的局部斜率确定对边缘进行微分的方向，将血管相邻部分图像灰度进行微分，按微分最大求取边缘点，最后采用B样条函数对边缘点进行平滑，最终得到血管的边缘线。     

医学图象位面行程编码实时压缩策略

本文研究了医学图象的位面行程编码及其硬件实现方案，用于动态图象（２５帧／秒）的不失真实时压缩和恢复，以熵为指标对几种图象信源的描述形式进行评价后表明，采用位面结构描述信源更有利于提高压缩效率。利用我们提出的一种定长行程码方法对ＣＴ图象进行位面行程编码压缩，其压缩比显著提高。并研制了基于此方法的编码器和恢复器。     

真彩色图象边缘检测技术在胃镜图中的应用

目前计算机图象处理技术中，边缘检测已有许多成熟的算法、能较好地完成图象分割的任务。但在医学图象中、有些病变区域的边缘很难确定，人眼判断有很大的主观性。用传统的边缘检测技术不会取得好的检测效果。为此，本文针对胃镜图象中胃溃疡边缘的自动检测提出了一种径向搜索算法、成功地解决了计算机自动边缘检测问题，为病变区域的差别与测量提供了客观依据。     

图像处理方法用于离体培养乳鼠心肌细胞动态特征分析

通过对离体培养的心肌细胞特征参数的定量分析,从细胞力学和分子生物学的角度研究药物的作用机理,是目前生物医学工程学科的前沿性课题。心肌细胞在不受外力作用的情况下具有自主搏动特性,使得对于它的动态分析更有意义。介绍了用于心肌细胞动态特征分析的图像采集处理系统,以及运用图像分析算法能够获得的各种动态特征参数,包括搏动频率、搏动周期、收缩幅度、形态面积变化等。     

边缘检测微分算子的分析及在医学图像中的应用

边缘检测是医学图像处理必不可少的一步 ,采用微分算子检测边缘是最常用也是处理效果比较好的一种方法。我们从频域角度出发 ,分析了 Roberts算子、Prewitt算子、Sobel算子以及拉普拉斯算子的频谱特性。提出了在使用和构造微分算子时 ,要充分考虑它们的频谱特性。不同的微分算子对不同边缘检测的敏感程度是不同的 ,因此对不同类型的边缘提取 ,应该采用对此类型边缘敏感的算子进行边缘提取。最后通过实际的 MRI图像处理验证了边缘检测算子选择的重要性。     

Medical Image Tamper Detection Based on Passive Image Authentication

Telemedicine has gained popularity in recent years. Medical images can be transferred over the Internet to enable the telediagnosis between medical staffs and to make the patient’s history accessible to medical staff from anywhere. Therefore, integrity protection of the medical image is a serious concern due to the broadcast nature of the Internet. Some watermarking techniques are proposed to control the integrity of medical images. However, they require embedding of extra information (watermark) into image before transmission. It decreases visual quality of the medical image and can cause false diagnosis. The proposed method uses passive image authentication mechanism to detect the tampered regions on medical images. Structural texture information is obtained from the medical image by using local binary pattern rotation invariant (LBPROT) to make the keypoint extraction techniques more successful. Keypoints on the texture image are obtained with scale invariant feature transform (SIFT). Tampered regions are detected by the method by matching the keypoints. The method improves the keypoint-based passive image authentication mechanism (they do not detect tampering when the smooth region is used for covering an object) by using LBPROT before keypoint extraction because smooth regions also have texture information. Experimental results show that the method detects tampered regions on the medical images even if the forged image has undergone some attacks (Gaussian blurring/additive white Gaussian noise) or the forged regions are scaled/rotated before pasting.     

Fractional calculus in bioengineering, part 2

Fractional calculus (integral and differential operations of noninteger order) is not often used to model biological systems. Although the basic mathematical ideas were developed long ago by the mathematicians Leibniz (1695), Liouville (1834), Riemann (1892), and others and brought to the attention of the engineering world by Oliver Heaviside in the 1890s, it was not until 1974 that the first book on the topic was published by Oldham and Spanier. Recent monographs and symposia proceedings have highlighted the application of fractional calculus in physics, continuum mechanics, signal processing, and electromagnetics, but with few examples of applications in bioengineering. This is surprising because the methods of fractional calculus, when defined as a Laplace or Fourier convolution product, are suitable for solving many problems in biomedical research. For example, early studies by Cole (1933) and Hodgkin (1946) of the electrical properties of nerve cell membranes and the propagation of electrical signals are well characterized by differential equations of fractional order. The solution involves a generalization of the exponential function to the Mittag-Leffler function, which provides a better fit to the observed cell membrane data. A parallel application of fractional derivatives to viscoelastic materials establishes, in a natural way, hereditary integrals and the power law (Nutting/Scott Blair) stress-strain relationship for modeling biomaterials. In this review, I will introduce the idea of fractional operations by following the original approach of Heaviside, demonstrate the basic operations of fractional calculus on well-behaved functions (step, ramp, pulse, sinusoid) of engineering interest, and give specific examples from electrochemistry, physics, bioengineering, and biophysics. The fractional derivative accurately describes natural phenomena that occur in such common engineering problems as heat transfer, electrode/electrolyte behavior, and sub-threshold nerve propagation. By expanding the range of mathematical operations to include fractional calculus, we can develop new and potentially useful functional relationships for modeling complex biological systems in a direct and rigorous manner. In Part 1 of this review (Crit Rev Biomed Eng 2004; 32(1):1-104), the fundamental properties of fractional calculus were introduced. The reader should refer to that material, particularly the sections on special functions and fractional order differential equations, for background.     

基于操作指令同步的医学影像远程会诊系统

在现有的远程会诊系统中,有的需要专用线路和设备,成本十分昂贵;有的采用基于NetMeeting的系统,不管通过电子白板或应用程序共享的方式,都不能直接在医学图像上操作或在一个应用程序窗口中同步操作,达不到会诊双方在阅片室的同一台阅片灯上进行现场交互的效果;因此应用起来有很大的局限性.我们开发了基于“操作指令远程同步”的影像远程会诊系统，改善了上述系统中的不足，使会诊双方在一方的图像处理和标识等操作通过预定的同步指令同步到对方，达到现场会诊的效果。     

Boundary detection in carotid ultrasound images using dynamic programming and a directional Haar-like filter

The intima-media thickness (IMT) of the carotid artery, obtained from B-mode ultrasound images, has recently been proposed as one of the most useful indices of atherosclerosis and can also be used to predict major cardiovascular events. Ultrasonic measurements of the IMT are conventionally obtained by time-consuming manual tracing of the interfaces between tissue layers. We propose a computerized method to detect the boundary of the intima-media complex using a directional Haar-like filter that can account for the slope of the boundary in an image. The directional Haar-like filter extracts a directional boundary feature as an image feature in the region of interest, which is used to compute a cost function. A cost function includes not only the directional Haar-like filtering value but also the geometric continuity that is computed for every pixel in the region of interest. The optimal boundary pixels are detected by using a dynamic programming approach that searches for the pixel that minimizes the cost function in each column of the image. We compared the performance of the proposed method with that of manual methods performed by two radiologists. The results showed that our approach produces very similar results to those based on manual tracing, and there was no statistically significant difference between the IMT measurements segmented manually and those analyzed using our method.     

神经元网络容错学习在肾小球区域边界增强中的应用

在肾脏组织切片图像的自动分析系统中，肾小球区域边界的增强是一个关键的环节。肾组织切片图像的复杂特点导致了对肾小球边界特征描述的困难。本文在给出特殊边界定义下提出了一种特征模板，用神经元网络构造非线性阈值曲面，考虑网络容错性对边界增强效果的影响，选择合适的阈值曲面进行边界增强。实验结果表明，该容错学习可以在抑制噪声的同时获得对肾小球边界的增强，从而获得良好的处理效果，并且对染色程度不同的样本图像具有强的适应性。