Palm print image recovery and de-noising via multi-channel wavelet filter bank

In this paper, a 3-channel wavelet transform method is introduced to recover palm print images following serious deformation. The deformation processing is actually a kind of digital re-sampling. A filter bank consisting of three filters is implemented for wavelet decomposition of the palm print image, and then a procedure of binary interpolation is performed after the image is reconstructed by another filter bank consisting of another three filters. The design of multi-channel wavelet filter bank is based on the Quadrature Mirror Filter (QMF) method. Because the noise is caused by the Morie stripe, the images are further de-noised after the geometry deformation is addressed. Acceptable results have been obtained.     

Selection of biorthogonal filters for image compression of MR images using wavelet packets

We present an analysis of different filter banks for the compression of magnetic resonance (MR) images of the human brain using wavelet packets based on biorthogonal filters. Initially, peak signal to noise ratio (PSNR) and normalized root mean square (RMS) error criteria are calculated for a series of images compressed with a 33:1 ratio, using filter banks based on biorthogonal wavelet packets. The results lead us to choose a few of these filter banks as optimal for image compression. One of these filters is employed to compress several images at four different compression ratios: 12.5:1, 25:1, 37.5:1 and 50:1. The quality of these images was evaluated by visual analysis by a group of seven experts who graded image quality on a 0-7 scale. Results show that using these filters, we can compress images to a rate of around 30:1 without introducing noticeable differences. Other applications for these filters are currently under study and include the compression/fusion of MR image stacks in order to obtain even better reductions in the amount of data needed to reconstruct complete MRI studies.     

Highly resolved diffuse optical tomography: a systematic approach using high-pass filtering for value-preserved images

We attempt to develop a systematic scheme through adopting high-pass filtering (HPF) to well resolve value-preserved images such as medical images. Our approach is derived from the Poisson maximum a posteriori superresolution algorithm employing the HP filters, where four filters are considered such as two low-pass-filter-combination based filters, wavelet filter, and negative-oriented Laplacian HP filter. The proposed approach is incorporated into the procedure of finite-element-method (FEM)-based image reconstruction for diffuse optical tomography in the direct current domain, posterior to each iteration without altering the original FEM modeling. This approach is justified with various HPF for different cases that breast-like phantoms embedded with two or three inclusions that imitate tumors are employed to examine the resolution performances under certain extreme conditions. The proposed approach to enhancing image resolution is evaluated for all tested cases. A qualitative investigation of reconstruction performance for each case is presented. Following this, we define a set of measures on the quantitative evaluation for a range of resolutions including separation, size, contrast, and location, thereby providing a comparable evaluation to the visual quality. The most satisfactory result is obtained by using the wavelet HP filter, and it successfully justifies our proposed scheme.     

Nonlinear filters applied on computerized axial tomography: theory and phantom images.

New nonlinear image processing techniques, in particular smoothing based on the understanding of the image, may create computerized tomography (CT) images of good quality using less radiation. Such techniques may be applied before the reconstruction and particularly after it. Current CT scanners use strong linear low-pass filters applied to the CT projections, reducing noise but also deteriorating the resolution of the image. The method in this study was to apply a weak low-pass filter on the projections, to perform the reconstruction, and only then to apply a nonlinear filter on the image. Various kinds of nonlinear filters were investigated based on the fact that the image is approximately piecewise constant. The filters were applied with many values of several parameters and the effects on the spatial resolution and the noise reduction were evaluated. The signal-to-noise ratio of a high-contrast phantom image processed were compared with the nonlinear filter, with the SNR of the phantom images obtained with the built-in CT linear filters in two scanning modes, the normal and the ultra high resolution modes. It was found that the nonlinear filters improve the SNR of the image, compared to the built-in filters, about three times for the normal mode and twice for the UHR scanning mode. The most successful filter on low-contrast phantom image was applied and it also seems to lead to promising results. These results seem to show that applying nonlinear filters on CT images might lead to better image quality than using the current linear filters.(ABSTRACT TRUNCATED AT 250 WORDS)     

Homomorphic wavelet thresholding technique for denoising medical ultrasound images

A novel homomorphic wavelet thresholding technique for reducing speckle noise in medical ultrasound images is presented. First, we show that the speckle wavelet coefficients in the logarithmically transformed ultrasound images are best described by the Nakagami family of distributions. By exploiting this speckle model and the Laplacian signal prior, a closed form, data-driven, and spatially adaptive threshold is derived in the Bayesian framework. The spatial adaptivity allows the additional information of the image (such as identification of homogeneous or heterogeneous regions) to be incorporated into the algorithm. Further, the threshold has been extended to the redundant wavelet representation, which yields better results than the decimated wavelet transform. Experimental results demonstrate the improved performance of the proposed method over other well-known speckle reduction filters. The application of the proposed method to a realistic US test image shows that the new technique, named HomoGenThresh, outperforms the best wavelet-based denoising method reported in [1] by more than 1.6 dB, Lee filter by 3.6 dB, Kaun filter by 3.1 dB and band-adaptive soft thresholding [2] by 2.1 dB at an input signal-to-noise ratio (SNR) of 13.6 dB.     

冠状动脉造影图像降噪处理的3种方法比较

目的 对冠状动脉造影图像降噪处理的3种方法进行比较。方法 将冠状动脉造影图像数字化并输入计算机，然后再用中值滤波法，自适应滤波法和基于小波变换的降噪处理3种方法分别处理同一图像，比较效果。结果 成功地运用了3种方法对冠状动脉造影图像进行降噪处理，图像质量均有所提高。结论 自适应降噪处理和基于小波系数的降噪处理结果较好，但自适应降噪处理的速度要快。     

肝包虫病和肝囊肿CT图像的分型研究

探讨计算机辅助诊断技术在肝包虫病和肝囊肿CT图像分型中的应用。方法 对单囊型肝包虫病和单发性肝囊肿CT图像感兴趣区域,分别使用传统的预处理方法和图像融合方法,提取原始ROI、预处理后的和融合后的ROI图像Haar小波、DB2小波、Tamura、Gabor滤波器和灰度-梯度共生矩阵特征,通过支持向量机和BP神经网络分类模型分类,比较三种方法的分类准确率,并对各分类模型进行参数评估。结果 从原始ROI图像直接提取的Haar小波、DB2小波、Tamura和GGCM特征的最佳分类准确率均达到了95%以上;融合后的ROI图像五种特征的分类准确率都较高,在90%以上。结论 本研究所使用的方法应用于肝包虫病和肝囊肿CT图像的分型中具有一定的分类优势,为影像学诊断提供依据。     

肿瘤皮纹无损检测分析系统中的掌纹图像处理

根据方便、快捷、无损伤、无痛苦的原则，正在研制数字化肿瘤皮纹学无损检测分析系统。此系统的技术基础取决于掌纹图像处理。但是，通过FPS—1指纹／掌纹摄取仪得到的待识别掌纹图像并不清晰；(1)由于手掌中部凹陷处不能与摄取仪完全接触，造成待识别掌纹图像中间区域出现断连；(2)由于人的手掌按住掌纹摄取装置时。用力过猛或过轻，都会造成待识掌纹图中各特征点相互之间的距离变化、灰度值变化及其本身在坐标系中的位置变化，即所谓的畸变；(3)存在着大量的汗腺点，它们均被视为噪音。为了解决这些问题，并且针对掌纹图像特点，文中提出了相应的改进的图像处理算法。结果表明，在保留大部分细节特征的前提下，可以清楚的辨别嵴纹结构。这些工作为提取掌纹特征，特别是掌纹三叉点的定位，莫定了良好的基础。     

Enhancing obstetric and gynecology ultrasound images by adaptation of the speckle reducing anisotropic diffusion filter

OBJECTIVE: So far there is no ideal speckle reduction filtering technique that is capable of enhancing and reducing the level of noise in medical ultrasound (US) images, while efficiently responding to medical experts' validation criteria which quite often include a subjective component. This paper presents an interactive tool called evolutionary speckle reducing anisotropic diffusion filter (EVOSRAD) that performs adaptive speckle filtering on ultrasound B-mode still images. The medical expert runs the algorithm interactively, having a permanent control over the output, and guiding the filtering process towards obtaining enhanced images that agree to his/her subjective quality criteria. METHODS AND MATERIAL: We employ an interactive evolutionary algorithm (IGA) to adapt on-line the parameters of a speckle reducing anisotropic diffusion (SRAD) filter. For a given input US image, the algorithm evolves the parameters of the SRAD filter according to subjective criteria of the medical expert who runs the interactive algorithm. The method and its validation are applied to a test bed comprising both real and simulated obstetrics and gynecology (OB/GYN) ultrasound images. RESULTS: The potential of the method is analyzed in comparison to other speckle reduction filters: the original SRAD filter, the anisotropic diffusion, offset and median filters. Results obtained show the good potential of the method on several classes of OB/GYN ultrasound images, as well as on a synthetic image simulating a real fetal US image. Quality criteria for the evaluation and validation of the method include subjective scoring given by the medical expert who runs the interactive method, as well as objective global and local quality criteria. CONCLUSIONS: The method presented allows the medical expert to design its own filters according to the degree of medical expertise as well as to particular and often subjective assessment criteria. A filter is designed for a given class of ultrasound images and for a given medical expert who will later use the respective filter in clinical practice. The process of designing a filter is simple and employs an interactive visualization and scoring stage that does not require image processing knowledge. Results show that filters tailored using the presented method achieve better quality scores than other more generic speckle filtering techniques.     

一种新的超声图像斑点噪声抑制方法

斑点噪声是超声图像中固有的噪声。现有的用于斑点噪声抑制的自适应滤波方法,小波软阈值方法及小波域内细节抛弃法在去除噪声的同时,不同程度地丢失了一些图像细节。针对这一问题。本文提出了一种新的结合自适应中值滤波和小波软阈值处理的超声图像斑点噪声抑制方法。对计算机仿真图像及超声图像进行处理的结果表明,本文提出的新方法在有效去除斑点噪声的同时,很好地保留了图像的细节,优于上述的其他方法。     

基于自由变形法的多模态医学图像的配准与融合

本研究提出了一种自动识别颈部PET-CT图像特征点的算法，它应用自由变形（FFD）方法以CT图像的特征点为参考使PET图像产生变形，再结合最大互信息法对颈部PET与CT图像进行非刚体配准，最后用改进的小波图像融合法把两者进行融合得出视觉效果比较理想的融合图像。经实际计算得出的变形PET图像与对应CT图像的互信息量大于原始PET图像，并且最后用改进的小波图像融合法得出的融合图像的信息量比一般小波融合大，由此证明本研究所用方法是有效的。     

CHO数字观察器在PET图像滤波方法评估中的应用

在临床应用中需要限制扫描时间和药物剂量,这往往会使正电子发射断层扫描(PET)的图像的分辨率变低,噪声变多。为提供可供临床诊断的图像,去噪是一个必须的手段,而在重建后增加一个滤波器是目前最常用的去噪方法。因此对不同滤波器滤波效果的比较是PET图像重建中的重要环节,其中最关键的是滤波参数的选取。目前采用的信噪比(SNR)以及恢复系数(RC)等评估方法可以用来非定量地选取参数,研究者们只能凭经验选取最优参数。而通道化霍特林观察器(CHO)作为一个比较通用的数字观察器,已被用于与PET图像质量相关的各种参数的选择,如重建算法参数、系统设计参数、临床协议参数等,然而其在评估不同滤波方法对图像重建质量的影响中的应用研究还比较少。通过比较CHO计算得到的ROC(receiver operating characteristic)曲线下面积(area under the ROC curve,AUC),选择两种常用的滤波器(即高斯滤波器和非局部均值(Non-Local Mean, NLM)滤波器)的最优参数,并评估它们在PET中的滤波效果。结果表明,对于13 mm球体,σ为1.1~1.4的高斯滤波器和f为0.5~0.9的NLM滤波器可以达到最大的检测能力值,而对于10 mm球体,σ为1.4~2.0的高斯滤波器和f为0.5~0.9的NLM滤波器可以达到最大的检测能力值。虽然两个滤波器所对应的AUC值都能高达0.9,但是NLM滤波器的AUC值高于高斯滤波器。通过IEC图像和病人图像也能发现,NLM滤波后的PET图像中的亮点比高斯滤波的更加清晰,噪声更少。该结论和传统滤波器评估方法得到的结论一致,这说明在PET的病灶检测任务中,CHO能够准确地比较这两种滤波器的性能。     

Image filtering for improved dose resolution in CT polymer gel dosimetry

X-ray computed tomography (CT) has been established as a feasible method of performing dosimetry using polyacrylamide gels (PAGs). A small density change occurs in PAG upon irradiation that provides contrast in PAG CT images. However, low dose resolution limits the clinical usefulness of the technique. This work investigates the potential of using image filtering techniques on PAG CT images in order to reduce image noise and improve dose resolution. CT image noise for the scanner and protocol used for the gel images is analyzed and found to be Gaussian distributed and independent of the contrast level in the images. As a result, several filters for reducing spatially invariant noise are investigated: mean, median, midpoint, adaptive mean, alpha-trimmed mean, sigma mean, and a relatively new filter called SUSAN (smallest univalue segment assimilating nucleus). All filters are applied, using 3x3, 5x5, and 7x7 pixel masks, to a CT image of a PAG irradiated with a stereotactic radiosurgery dose distribution. The dose resolution within 95% confidence (D(delta)95%) is calculated and compared for each filtered image, as well the unfiltered image. In addition, the ability of the filters to maintain the spatial integrity of the dose distribution is evaluated and compared. Results clearly indicate that the filters are not equal in their ability to improve D(delta)95% or in their effect on the spatial integrity of the dose distribution. In general, increasing mask size improves D(delta)95% but simultaneously degrades spatial dose information. The mean filter provides the greatest improvement in D(delta)95%, but also the greatest loss of spatial dose information. The SUSAN, mean adaptive, and alpha-trimmed mean filters all provide comparable, but slightly poorer dose resolution. In addition, the SUSAN and adaptive filters both excel at maintaining the spatial distribution of dose and overall are the best performing filters for this application. The midpoint filter, normally useful for Gaussian noise, is poor all-round, dramatically distorting the dose distribution for masks greater than 3x3. The median filter, a common edge preserving noise reduction filter, performs moderately well, but artificially increases high dose gradients. The sigma filter preserves the spatial distribution of dose very well but is least effective at improving dose resolution. In summary, dose resolution can be significantly improved in CT PAG dosimetry through postprocessing of CT images using spatial noise reduction filters. However, such filters are not equal in their ability to improve dose resolution or to maintain the spatial integrity of the dose distribution and an appropriate filter must be chosen depending on clinical demands of the application.     

Oversampled filters for quantitative volumetric PET reconstruction

Three-dimensional filtered backprojection uses filters generally specified in the Fourier domain. Implementing these filters by direct sampling in the Fourier domain produces an artifact in the reconstructed images consisting primarily of a DC shift. This artifact is caused by aliasing of the reconstruction filter. We have developed a filter construction technique using Fourier domain oversampling, which reduces the artifact. A method to construct the filter efficiently without the need to create and store the entire oversampled filter array is also presented. Quantitative accuracy in filtered backprojection is of particular importance in multiple-pass algorithms used to reconstruct data from cylindrical PET scanners. We are able to implement such algorithms without fitting the reprojected views to the scanner data.     

Identification of palm print using dermatoglyphics analysis and detection system

This paper investigated the biological characteristics of palm print. The preprocessing plays an important role in identifying the ridge characteristics of palm due to the complexity and poor quality of the images. As a functional plug-in of the dermatoglyphics analysis and detection system, the template-based image preprocessing was proposed in this study, including histogram redistribution, ridge orientation, and skeletonization. Using this system, the automatic identification of ridges and triradiuses was accomplished with an effective result. The study demonstrated the feasibility of the method and the potential of the system for being applied as an auxiliary diagnostic tool for heredity diseases (e.g. mammary cancer and neurofibromatosis).     

基于形态学重构的超声医学图像滤波方法

Speckle噪声是造成超声医学图像质量下降的最主要原因。我们通过修改形态学重构算法-Downhill算法的初始条件,使其适用于超声医学图像的去噪处理。首先在掩模图像中确定标记图像作为算法的初始化和开始区域,再使用改进的Downhill算法对超声医学图像进行滤波处理。实验结果表明,与其他3种传统滤波方法相比,该方法能快速有效地去除心脏腔室内的Speckle噪声同时保留图像的轮廓细节信息。     

A unified design algorithm of two-dimensional digital filters for radioisotope image processing

A unified design algorithm of two-dimensional digital filters for radioisotope image processing based on the Fourier-Bessel transform and the weighted least-squares method is described. The algorithm presented here can treat the various kinds of two-dimensional digital filters in a unified approach. Design examples are presented and several graphs are included to show the relationships between the design parameters as an aid in practical applications. The application of the method in radioisotope image processing is also presented. Several low-pass, Wiener and band-pass filters were designed using the method and applied to some clinical data in nuclear medicine including SPECT images. The digital filter design technique proposed here is considered to provide a powerful tool for extraction of additional qualitative information and improvement of the quality of nuclear medicine images both in research and in routine clinical work.     

Medical feature based evaluation of structuring elements for morphological enhancement of ultrasonic images

This paper investigates the use of morphology-based nonlinear filters, and performs deterministic and statistical analysis of the linear combinations of the filters for the image quality enhancement of B-mode ultrasound images. The fact that the structuring element shape greatly influences the output of the filter, is one of the most important features of mathematical morphology. The present reported work comparatively evaluates the structuring elements for morphological liver image enhancement and verifies the hypothesis that the speckles visible in US images are short, slightly ‘banana-shaped’ white lines. Initially, five different liver images were morphologically filtered using 10 different structuring elements and then the filtered images were assessed quantitatively. Image quality parameters such as peak signal-to-noise ratio, mean square error and correlation coefficient have been used to evaluate the performance of the morphological filters with different structuring elements. To endorse the observation of the quantitative analysis, the filtered images were then evaluated qualitatively, based on the image features looked into by the medical fraternity. The evaluation parameters have been taken on the basis of the suggestions made by a group of radiologists. The results of the processed images were then evaluated by a different group of radiologists. A multi-point rank order method has been used to identify small differences or trends in observation. The subjective analysis by radiologists indicates that morphological filter using line shaped structuring element with length 2 performs better than the other structuring elements. These observations were found to be in line with the observations of quantitative analysis.     

基于小波变换结合其他预处理方法的周围型早期肺癌CT图像增强研究

探讨增强早期肺癌CT图像的方法.采用小波变换增强图像细节的方法,根据图像特点,同时结合对比度自适应直方图均衡化或(和)自适应滤波去噪法,对10位早期周围型肺癌患者的50张CT图像进行增强.结果表明,处理后图像中肺内结节的边缘锐利、内部密度清晰、周围征象(如胸膜凹陷征等)清楚;各组织器官边缘清晰、层次明显,肺纹理清晰度增加.尤其是低对比度图像,处理后图像质量有较明显提高.基于小波变换结合其他预处理方法,对早期肺癌的CT图像进行增强,可为同类研究提供一定的参考.