ROI-based reversible watermarking scheme for ensuring the integrity and authenticity of DICOM MR images

Multimedia Tools and Applications - Reversible and imperceptible watermarking is recognized as a robust approach to confirm the integrity and authenticity of medical images and to verify that...     

Enhancing data authenticity and integrity in P2P systems

Peer-to-peer systems let users share information in distributed environments because of their scalability and efficiency. However, existing P2P systems are vulnerable to numerous security attacks and lack a mechanism to ensure shared information's authenticity and integrity. A proposed general architecture enhances these aspects by leveraging trusted computing technology, which is built on a trusted platform module and provides a mechanism for building trust into the application layer. Preliminary experimental results show that the proposed scheme can ensure data authenticity and integrity in P2P systems with acceptable performance overhead.     

融合特征和先验知识的车牌字符图像检测算法

提出一种融合车牌字符切割后的二值字符图像的结构特征及对应的彩色小字符图像的颜色信息对车牌分割后的小字符图像进行真伪字符图像区分,以此达到检测字符图像目的的算法。为满足实时车牌对时间响应的要求,对车牌字符切割得到的灰度图像作快速二值化,在二值化的图像上提取结构信息,结合车牌字符分布的特点去除了大部分非颜色车牌的伪字符图像。对于难以从结构上进行字符检测的颜色车牌伪字符图像,在结构特征分析的基础上再次通过从彩色图像提取的颜色信息进行相似性分析,排除伪字符图像。对候选字符图像融合大间隔这个先验知识得到输出的字符图像。实验结果表明算法有良好的字符检测效果,可以用于实时车牌识别系统中作为字符切割后期处理一部分。     

A system for pattern recognition and pattern summarization in multi-band satellite images

A new system (C.T.R.F.’s LSGENSYS—Linguistic Summary Generation System) that has been developed for pattern recognition and summarization of patterns in multiband (RGB) satellite images is described in this paper. The system design is described in some detail. The system has been tested successfully with SPOT MS and LANDSAT images. It extracts, analyzes, and summarizes patterns such as land, island, water body, river, fire, and urban settlements from these images. The results are presented by allowing the system to automatically classify and interpret these images. Some elements of supervised classification are also introduced, and a comparison is made between the results in each case. The text was submitted by the author in English. Hema Nair. Date of Birth: November 21, 1965. Education: Hema Nair received her Bachelors Degree in Electrical Engineering from Government Engineering College, University of Calicut, Kerala, India, in 1986. She received her Masters Degree in Electrical Engineering from National University of Singapore in 1993. Ms. Nair received her Masters Degree in Computer Science from Clark Atlanta University, Atlanta, United States, in 1996. Membership: A member of IEEE (USA) and ACM (USA) since 1997. A member of the Institution of Engineers (India) since 1988. Awards: 1. Ms. Nair’s Masters Degree research in the United States was funded by a US Army Grant. 2. One of Ms. Nair’s publications was cited with the Abstract in NASA’s Scientific and Technical Information Program Reports of 2006. Work Experience: 1. Ms. Nair was employed as Senior Technical Associate II at AT and T, New Jersey, United States, between 1996 and 2000. Her work included research and leading AT&T Projects as Project Leader. 2. She also served as Faculty in Apple Information Technology, Ltd, Bangalore, India, between 1987 and 1990. 3. Ms. Nair worked on contract as a lecturer in Multimedia University, Malaysia, between 2001 and 2005. 4. Since 2005, she has been working as a Researcher at C.T.R.F., a research and education foundation in India. Research Interests: Ms. Nair’s research interests include Image Analysis, Pattern Recognition, Databases, Artificial Intelligence, and Data Mining. Publications: Ms. Nair has published several papers internationally. These include 7 International Conference Papers and 4 International Journals. Reviewer for LASTED International Conference 2004.     

Embedding in medical images with contrast enhancement and tamper detection capability

This paper presents an efficient data hiding technique capable of providing improved visual quality of watermarked images, besides having the ability to detect the tamper, if any. It is a spatial domain approach in which major emphasis is on improving the visual quality rather than increasing the PSNR or the embedding capacity. The medical images have been divided into Region of Interest (ROI) and Non-Region of Interest (NROI). Bringing out details that lie within the low dynamic range is very important in medical images for effective diagnosis. ROI being diagnostically critical region is enhanced using contrast stretching and subsequently, data is reversibly embedded into the peak bins of ROI. Only those peak bins are employed for reversible data embedding that have an adjacent empty bin to overcome the problem of overflow and underflow. In NROI, the uniform intensity and redundant information region, Least Significant Bit (LSB) embedding is employed for increasing the payload. For tamper detection, a fragile watermark has been embedded in the ROI. To evaluate the scheme various parameters like peak signal to noise ratio (PSNR), No-Reference Quality Metric for contrast-distorted images (NR-CDIQA) and Structural Similarity Index Matrix (SSIM) have been calculated. The experimental results show a remarkable increase in visual quality compared to state-of-art.

     

A bayesian approach to deformed pattern matching of iris images

We describe a general probabilistic framework for matching patterns that experience in-plane nonlinear deformations, such as iris patterns. Given a pair of images, we derive a maximum a posteriori probability (MAP) estimate of the parameters of the relative deformation between them. Our estimation process accomplishes two things simultaneously: it normalizes for pattern warping and it returns a distortion-tolerant similarity metric which can be used for matching two nonlinearly deformed image patterns. The prior probability of the deformation parameters is specific to the pattern-type and, therefore, should result in more accurate matching than an arbitrary general distribution. We show that the proposed method is very well suited for handling iris biometrics, applying it to two databases of iris images which contain real instances of warped patterns. We demonstrate a significant improvement in matching accuracy using the proposed deformed Bayesian matching methodology. We also show that the additional computation required to estimate the deformation is relatively inexpensive, making it suitable for real-time applications     

A procedure to prove statements in differential geometry

An algorithm for theorem proving in differential geometry based on the calculation of the differential dimension of differential quasi-algebraic sets is shown. In the case in which only ordinary differential equations are involved, an algorithm for such computation is presented. Different notions of validity for differential geometry statements are also compared.This paper was supported by Italian M.P.I. (40% 1985).     

A grammar of integrity constraints in medical documentation systems

An essential aspect for the utilization of medical data is their quality, thus a main feature of computer-based medical documentation systems should be to assist the user in complete and plausible data acquisition and maintenance. In this paper we define a grammar for modeling medical documentation systems to increase integrity and completeness of collected data, focusing attention on integrity constraints. An integrity constraint defines requirements that involved entities had to comply with. Furthermore it defines possibly implications in case of failure. The constraints presented in this paper are type constraint, length constraint, domain constraint, key constraint, quantity constraint, reference constraint, search constraint, result constraint, hierarchy constraint, and semantic constraint. Their grammar is declared using a schema in extensible markup language-format (XML-schema). The model introduced here can be used in computer-aided design and implementation of clinical documentation both minimizing effort and ensuring data quality, which was tested by an evaluation based on a specification of a registry for HIV-infected patients.     

Contour segmentation in 2D ultrasound medical images with particle filtering

Object segmentation in medical images is an actively investigated research area. Segmentation techniques are a valuable tool in medical diagnostics for cancer tumours and cysts, for planning surgery operations and other medical treatment. In this paper, a Monte Carlo algorithm for extracting lesion contours in ultrasound medical images is proposed. An efficient multiple model particle filter for progressive contour growing (tracking) from a starting point is developed, accounting for convex, non-circular forms of delineated contour areas. The driving idea of the proposed particle filter consists in the incorporation of different image intensity inside and outside the contour into the filter likelihood function. The filter employs image intensity gradients as measurements and requires information about four manually selected points: a seed point, a starting point, arbitrarily selected on the contour, and two additional points, bounding the measurement formation area around the contour. The filter performance is studied by segmenting contours from a number of real and simulated ultrasound medical images. Accurate contour segmentation is achieved with the proposed approach in ultrasound images with a high level of speckle noise.     

多阈值优化交互式分割算法及其在医学图像中的应用

针对交互式图像分割方法对边界模糊的医学图像进行分割时通常需要用户标记较多的初始种子或进行二次交互的不足,提出了一种简化标记的多阈值优化交互式分割算法。该算法在GrowCut交互式算法基础上通过引入图像灰度直方图的多个阈值自动生成初始种子模板,并利用改进的细胞自动机迭代算法实现图像分割。算法简化了用户操作,提高了分割精度。应用该算法分别对临床100张肝脏图像和牙菌斑图像进行分割,结果显示了该算法的良好性能。     

M估计在医学图像配准中的应用

图像的刚性配准或者匹配是图像处理中的热点和难点问题。由于图像的不连续性和成像设置中噪声的影响,传统的最小二乘方法（Least Squares Method）不能很好地解决这一难题。采用M估计算子（M-estimation operator）代替最小二乘算子,并结合由粗到精的多分辨率策略,提出了一种新的基于M估计的医学图像多分辨率配准算法,实验结果表明该方法对配准的速度、精度及鲁棒性都有很大的提高。     

Novel segmentation algorithm in segmenting medical images

The aim of this paper is to develop an effective fuzzy c-means (FCM) technique for segmentation of Magnetic Resonance Images (MRI) which is seriously affected by intensity inhomogeneities that are created by radio-frequency coils. The weighted bias field information is employed in this work to deal the intensity inhomogeneities during the segmentation of MRI. In order to segment the general shaped MRI dataset which is corrupted by intensity inhomogeneities and other artifacts, the effective objective function of fuzzy c-means is constructed by replacing the Euclidean distance with kernel-induced distance. In this paper, the initial cluster centers are assigned using the proposed center initialization algorithm for executing the effective FCM iteratively. To assess the performance of proposed method in comparison with other existed methods, experiments are performed on synthetic image, real breast and brain MRIs. The clustering results are validated using Silhouette accuracy index. The experimental results demonstrate that our proposed method is a promising technique for effective segmentation of medical images.     

Feature enhancement angiographic images in medical diagnosis

Multimedia Tools and Applications - This paper suggest three new proposed algorithms for the feature enhancement in the angiographic images. The first approach is based on mixing the features of...     

Knowledge-based analysis and understanding of medical images

Knowledge-based image analysis and interpretation of radiological images is of significant interest for several reasons including a means to identify and label each part of the image for further automated diagnostic analysis. Also, there is a need to develop a knowledge-based biomedical image analysis system which can analyze and interpret the anatomical images (such as those obtained from X-ray computed tomography (CT) scanning) in order to help analysis of functional images (such as those obtained from positron emission tomography (PET) scanning) of the organ of the same patient. This paper deals with the design and implementation of a knowledge-based system to analyze and interpret CT anatomical images of the human chest. In the approach presented here, the emphasis has been on the development of a strong low-level analysis system with the capability of analyzing in both bottom-up and top-down modes; and on the use of hierarchical relational, spatial, and structural knowledge of human anatomy in the process of high-level analysis and recognition.     

医学图像中微细管道结构的提取

以肝动脉提取为例,提出一种医学图像中微细管道结构的提取算法。算法主要步骤包括：最大亮度投影、二维管道提取、三维种子点生成和三维管道提取。算法对常规的区域生长法进行改进,提取效果与常规的区域生长法相比有较大改善。算法需要的人工干预很少,只需要指定四个参数。     

Frequency-based nonrigid motion analysis: application to fourdimensional medical images

We present a method for nonrigid motion analysis in time sequences of volume images (4D data). In this method, nonrigid motion of the deforming object contour is dynamically approximated by a physically-based deformable surface. In order to reduce the number of parameters describing the deformation, we make use of a modal analysis which provides a spatial smoothing of the surface. The deformation spectrum, which outlines the main excited modes, can be efficiently used for deformation comparison. Fourier analysis on time signals of the main deformation spectrum components provides a temporal smoothing of the data. Thus a complex nonrigid deformation is described by only a few parameters: the main excited modes and the main Fourier harmonics. Therefore, 4D data can be analyzed in a very concise manner. The power and robustness of the approach is illustrated by various results on medical data. We believe that our method has important applications in automatic diagnosis of heart diseases and in motion compression     

Simultaneous storage of patient information with medical images in the frequency domain

Digital watermarking is a technique of hiding specific identification data for copyright authentication. Most of the medical images are compressed by joint photographic experts group (JPEG) standard for storage. The watermarking is adapted here for interleaving patient information with medical images during JPEG compression, to reduce storage and transmission overheads. The text data is encrypted before interleaving with images in the frequency domain to ensure greater security. The graphical signals are also interleaved with the image. The result of this work is tabulated for a specific example and also compared with the spatial domain interleaving.