Tubular surface segmentation for extracting anatomical structures from medical imagery

This work provides a model for tubular structures, and devises an algorithm to automatically extract tubular anatomical structures from medical imagery. Our model fits many anatomical structures in medical imagery, in particular, various fiber bundles in the brain (imaged through diffusion-weighted magnetic resonance (DW-MRI)) such as the cingulum bundle, and blood vessel trees in computed tomography angiograms (CTAs). Extraction of the cingulum bundle is of interest because of possible ties to schizophrenia, and extracting blood vessels is helpful in the diagnosis of cardiovascular diseases. The tubular model we propose has advantages over many existing approaches in literature: fewer degrees-of-freedom over a general deformable surface hence energies defined on such tubes are less sensitive to undesirable local minima, and the tube (in 3-D) can be naturally represented by a 4-D curve (a radius function and centerline), which leads to computationally less costly algorithms and has the advantage that the centerline of the tube is obtained without additional effort. Our model also generalizes to tubular trees, and the extraction algorithm that we design automatically detects and evolves branches of the tree. We demonstrate the performance of our algorithm on 20 datasets of DW-MRI data and 32 datasets of CTA, and quantify the results of our algorithm when expert segmentations are available.     

Multifractal analysis of human retinal vessels

In this paper, it is shown that vascular structures of the human retina represent geometrical multifractals, characterized by a hierarchy of exponents rather then a single fractal dimension. A number of retinal images from the STARE database are analyzed, corresponding to both normal and pathological states of the retina. In all studied cases, a clearly multifractal behavior is observed, where capacity dimension is always found to be larger then the information dimension, which is in turn always larger then the correlation dimension, all the three being significantly lower then the diffusion limited aggregation (DLA) fractal dimension. We also observe a tendency of images corresponding to the pathological states of the retina to have lower generalized dimensions and a shifted spectrum range, in comparison with the normal cases.     

Detection and analysis of change in remotely sensed imagery withapplication to wide area surveillance

A new approach to wide area surveillance is described that is based on the detection and analysis of changes across two or more images over time. Methods for modeling and detecting general patterns of change associated with construction and other kinds of activities that can be observed in remotely sensed imagery are presented. They include a new nonlinear prediction technique for measuring changes between images and temporal segmentation and filtering techniques for analyzing patterns of change over time. These methods are applied to the problem of detecting facility construction using Landsat Thematic Mapper imagery. Full scene results show the methods to be capable of detecting specific patterns of change with very few false alarms. Under all conditions explored, as the number of images used increases, the number of false alarms decreases dramatically without affecting the detection performance. It is argued that the processing gain that results in using more than two images justifies the increased computational complexity and storage requirements of our approach over single image object detection and conventional change detection techniques.     

Detection of blood vessels in retinal images using two-dimensional matched filters

Blood vessels usually have poor local contrast, and the application of existing edge detection algorithms yield results which are not satisfactory. An operator for feature extraction based on the optical and spatial properties of objects to be recognized is introduced. The gray-level profile of the cross section of a blood vessel is approximated by a Gaussian-shaped curve. The concept of matched filter detection of signals is used to detect piecewise linear segments of blood vessels in these images. Twelve different templates that are used to search for vessel segments along all possible directions are constructed. Various issues related to the implementation of these matched filters are discussed. The results are compared to those obtained with other methods.     

Detection of changes in cell membrane structures using the Bioimprint technique

Recent advances in medical sciences have revealed the significance of cellular structures and morphology in biological function. A cell’s membrane represents the boundary between the cells and its environment. The variations in cell surface and morphologies may be used as indications of malfunction or even diseases. If abnormalities such as cancer can be detected at the molecular level this will offer an important means for early diagnosis using small numbers of cells. The use of electron and scanning probe microscopy such as atomic force microscopy (AFM) could facilitates the opportunity to study and examine the molecular processes of living cells in greater details. The difficulties faced in direct cellular analysis when using and operating the AFM in situ for morphological studies of the cells has led to the development of a novel approach called Bioimprint (Traut and Papanicolaou, 1941 [1]). Inspired by the high resolution of nanoimprint lithography processes, Bioimprint has been applied to a new area of biological cell replication for the purpose of imaging and analysis and has revealed some very important biological events when combined with AFM imaging. For this research, the structural features of endometrial cancer cells were investigated. Regulation of selected peptides were examined, especially those which are associated with angiogenic factors that promote the proliferation of nutrient-bearing blood vessels that support tumour growth. Using the Bioimprint technique which is a soft lithography process, an impression of the cell topology was created by applying a layer of monomer mixture onto the cells attached to a substrate and rapidly curing it under UV-light. Fast UV-radiation enables the imprint to lock cellular processes within minutes and replicas of the cancer cells exhibit structures down to nanometer scale. Cancer cells were cultured and incubated in accordance with standard biological culturing procedures and protocols approved by the New Zealand Human Ethics Committee. High-resolution AFM imagery provides the opportunity to examine the structure and topography of the cells closely so that any abnormalities can be identified. To study the replicated imprints, the features that resembled secretory pores on the AFM images were noted. The numbers of pores correlated well with levels of vascular endothelial growth factor (VEGF) that were secreted by the cells. Further experiments were conducted in which anti-VEGF-coated microbeads were observed in the AFM images to be attracted to the areas of the pores.     

Detection of new vessels on the optic disc using retinal photographs

Proliferative diabetic retinopathy is a rare condition likely to lead to severe visual impairment. It is characterized by the development of abnormal new retinal vessels. We describe a method for automatically detecting new vessels on the optic disc using retinal photography. Vessel-like candidate segments are first detected using a method based on watershed lines and ridge strength measurement. Fifteen feature parameters, associated with shape, position, orientation, brightness, contrast and line density are calculated for each candidate segment. Based on these features, each segment is categorized as normal or abnormal using a support vector machine (SVM) classifier. The system was trained and tested by cross-validation using 38 images with new vessels and 71 normal images from two diabetic retinal screening centers and one hospital eye clinic. The discrimination performance of the fifteen features was tested against a clinical reference standard. Fourteen features were found to be effective and used in the final test. The area under the receiver operator characteristic curve was 0.911 for detecting images with new vessels on the disc. This accuracy may be sufficient for it to play a useful clinical role in an automated retinopathy analysis system.     

Detection and classification of circular structures on SPOT images

An unsupervised method for detecting structural features on satellite images that consists of three major steps is proposed. The extraction of contours, which depends on the texture encountered is achieved by an iterative filtering followed by several thresholds that generate binary images. The detection of the structures from the contours involves four substeps: individualization of the curves; decomposition of the curves into subcircular elements; application of a version of the Hough transform to each subcircular element; and computation of precise results. The parameters that discriminate the structures are computed. These data allow the selection of different families of structures that are being looked at. The method has been applied to the region of Azru     

Morphological operations with iterative rotation of structuring elements for segmentation of retinal vessel structures

Multidimensional Systems and Signal Processing - The development of computer aided diagnosis system has a great impact on early and accurate disease diagnosis. The segmentation of retinal blood...     

基于背景估计和集成分类的眼底硬性渗出检测

眼底图像中硬性渗出的检测对于糖尿病性视网膜病变(简称"糖网")的早期诊断具有重要意义.为了实现眼底图像中硬性渗出物的自动检测,本文提出了一种结合背景估计和集成分类的眼底图像硬性渗出物自动检测方法.首先,对图像进行亮度校正、去噪、对比度增强等预处理操作,然后结合形态学方法进行背景估计和图像重建并移除视盘区域,得到渗出物候选区域.最后利用集成分类方法对候选区域进行分类,提取最终的硬性渗出区域.实验结果表明,本方法能够有效准确地检测到眼底图像中的硬性渗出物,对于糖网自动诊断技术的研究具有积极意义.     

Detection of polyomavirus DNA in human brain tumors

AIM: To investigate surgically resected human brain tumors for the presence of polyomavirus DNA. MATERIALS AND METHODS: 65 samples of surgically resected human brain tumors (57 tumors were of neuroectodermal genesis, 4--mesenchimal, 4--metastatic tumors) were examined for the presence of viral DNA by PCR analysis. RESULTS: DNA of polyomaviruses was found in oligodendroligomas (66.7% of cases), oligodendroastrocytomas (66.7% of cases) and glioblastomas (40% of cases). In metastatic tumors viral infection had not been detected. No correlation between the grade of brain tumors and infection with polyomavirus DNA has been revealed. CONCLUSION: Our data point to importance of investigation of the brain tumors and cerebrospinal fluid for determination of viral infection.     

红外图像中人体目标检测技术研究

针对红外序列图像中人体目标检测问题,采用了基于特征点的特征区域提取方法,先用FAST算法快速提取特征点,然后基于提取出的特征点,使用LBP算法提取特征区域,在得到感兴趣的特征区域（ROI区域）后,用对ROI区域进行基于离散小波变换的小波熵特征提取,并采用复合分类方法对ROI区域进行分类,利用此方法有效地将人体目标从红外序列图像中检测出来。     

Detection and measurement of retinal vessels in fundus images using amplitude modified second-order Gaussian filter

In this paper, the fitness of estimating vessel profiles with Gaussian function is evaluated and an amplitude-modified second-order Gaussian filter is proposed for the detection and measurement of vessels. Mathematical analysis is given and supported by a simulation and experiments to demonstrate that the vessel width can be measured in linear relationship with the "spreading factor" of the matched filter when the magnitude coefficient of the filter is suitably assigned. The absolute value of vessel diameter can be determined simply by using a precalibrated line, which is typically required since images are always system dependent. The experiment shows that the inclusion of the width measurement in the detection process can improve the performance of matched filter and result in a significant increase in success rate of detection.     

Efficient detection in hyperspectral imagery

Hyperspectral sensors collect hundreds of narrow and contiguously spaced spectral bands of data. Such sensors provide fully registered high resolution spatial and spectral images that are invaluable in discriminating between man-made objects and natural clutter backgrounds. The price paid for this high resolution data is extremely large data sets, several hundred of Mbytes for a single scene, that make storage and transmission difficult, thus requiring fast onboard processing techniques to reduce the data being transmitted. Attempts to apply traditional maximum likelihood detection techniques for in-flight processing of these massive amounts of hyperspectral data suffer from two limitations: first, they neglect the spatial correlation of the clutter by treating it as spatially white noise; second, their computational cost renders them prohibitive without significant data reduction like by grouping the spectral bands into clusters, with a consequent loss of spectral resolution. This paper presents a maximum likelihood detector that successfully confronts both problems: rather than ignoring the spatial and spectral correlations, our detector exploits them to its advantage; and it is computationally expedient, its complexity increasing only linearly with the number of spectral bands available. Our approach is based on a Gauss-Markov random field (GMRF) modeling of the clutter, which has the advantage of providing a direct parameterization of the inverse of the clutter covariance, the quantity of interest in the test statistic. We discuss in detail two alternative GMRF detectors: one based on a binary hypothesis approach, and the other on a "single" hypothesis formulation. We analyze extensively with real hyperspectral imagery data (HYDICE and SEBASS) the performance of the detectors, comparing them to a benchmark detector, the RX-algorithm. Our results show that the GMRF "single" hypothesis detector outperforms significantly in computational cost the RX-algorithm, while delivering noticeable detection performance improvement.     

Detection of optic disc in retinal images by means of a geometrical model of vessel structure

We present here a new method to identify the position of the optic disc (OD) in retinal fundus images. The method is based on the preliminary detection of the main retinal vessels. All retinal vessels originate from the OD and their path follows a similar directional pattern (parabolic course) in all images. To describe the general direction of retinal vessels at any given position in the image, a geometrical parametric model was proposed, where two of the model parameters are the coordinates of the OD center. Using as experimental data samples of vessel centerline points and corresponding vessel directions, provided by any vessel identification procedure, model parameters were identified by means of a simulated annealing optimization technique. These estimated values provide the coordinates of the center of OD. A Matlab prototype implementing this method was developed. An evaluation of the proposed procedure was performed using the set of 81 images from the STARE project, containing images from both normal and pathological subjects. The OD position was correctly identified in 79 out of 81 images (98%), even in rather difficult pathological situations.     

紫杉醇抑制原代培养人视网膜色素上皮细胞增殖的实验研究

目的研究紫杉醇(Taxol)对体外原代培养人视网膜色素上皮(human Retinal Pigment Epithelium,hRPE)细胞增殖的抑制作用及机制。方法体外分离、原代培养hRPE细胞,采用免疫细胞化学方法对其进行鉴定。不同浓度紫杉醇(0、0.005、0.05、0.5、5mg/L)处理hRPE细胞一定时间,采用形态学观察、细胞生长曲线及MTT法检测药物对hRPE细胞的生长抑制效应,流式细胞术检测药物对hRPE细胞的细胞周期阻滞作用及凋亡诱导作用。结果原代培养的hRPE细胞胞浆富含色素,随传代次数增加,黑色素颗粒逐渐减少直至消失。用抗人细胞角蛋白抗体进行免疫细胞化学鉴定hRPE细胞呈特异的阳性反应。细胞生长曲线及MTT法显示:紫杉醇作用于hRPE细胞24h和72h,其抑制细胞生长增殖的IC50值分别为5.24和3.24mg/L。流式细胞分析术检测结果显示:0.5mg/L紫衫醇作用细胞48h即可显著延迟hRPE细胞G2/M期进展并诱导凋亡(P<0.05)。透射电镜观察显示:0.5mg/L紫杉醇作用后细胞表面微绒毛减少,电子密度增加,细胞器减少,异染色质聚集成团、边聚等。结论紫杉醇通过阻滞G2/M期进展...     

Exploiting manifold geometry in hyperspectral imagery

A new algorithm for exploiting the nonlinear structure of hyperspectral imagery is developed and compared against the de facto standard of linear mixing. This new approach seeks a manifold coordinate system that preserves geodesic distances in the high-dimensional hyperspectral data space. Algorithms for deriving manifold coordinates, such as isometric mapping (ISOMAP), have been developed for other applications. ISOMAP guarantees a globally optimal solution, but is computationally practical only for small datasets because of computational and memory requirements. Here, we develop a hybrid technique to circumvent ISOMAP's computational cost. We divide the scene into a set of smaller tiles. The manifolds derived from the individual tiles are then aligned and stitched together to recomplete the scene. Several alignment methods are discussed. This hybrid approach exploits the fact that ISOMAP guarantees a globally optimal solution for each tile and the presumed similarity of the manifold structures derived from different tiles. Using land-cover classification of hyperspectral imagery in the Virginia Coast Reserve as a test case, we show that the new manifold representation provides better separation of spectrally similar classes than one of the standard linear mixing models. Additionally, we demonstrate that this technique provides a natural data compression scheme, which dramatically reduces the number of components needed to model hyperspectral data when compared with traditional methods such as the minimum noise fraction transform.     

Robust classification of blurred imagery

We present two novel approaches for the classification of blurry images. It is assumed that the blur is linear and space invariant, but that the exact blurring function is unknown. The proposed fusion-based approaches attempt to perform the simultaneous tasks of blind image restoration and classification. We call such a problem blind image fusion. The techniques are implemented using the nonnegativity and support constraints recursive inverse filtering (NAS-RIF) algorithm for blind image restoration and the Markov random field (RIRF)-based fusion method for classification by Schistad-Solberg et al. (see IEEE Trans. Geosci. Remote Sensing, vol.32, p.768-78, 1994). Simulation results on synthetic and real photographic data demonstrate the potential of the approaches. The algorithms are compared with one another and to situations in which blind blur removal is not attempted.