Rapid detection of camera tampering and abnormal disturbance for video surveillance system

Camera tampering may indicate that a criminal act is occurring. Common examples of camera tampering are turning the camera lens to point to a different direction (i.e., camera motion) and covering the lens by opaque objects or with paint (i.e., camera occlusion). Moreover, various abnormalities such as screen shaking, fogging, defocus, color cast, and screen flickering can strongly deteriorate the performance of a video surveillance system. This study proposes an automated method for rapidly detecting camera tampering and various abnormalities for a video surveillance system. The proposed method is based on the analyses of brightness, edge details, histogram distribution, and high-frequency information, making it computationally efficient. The proposed system runs at a frame rate of 20–30 frames/s, meeting the requirement of real-time operation. Experimental results show the superiority of the proposed method with an average of 4.4% of missed events compared to existing works.     

Functional Human Vascular Network Generated in Photocrosslinkable Gelatin Methacrylate Hydrogels

The generation of functional, 3D vascular networks is a fundamental prerequisite for the development of many future tissue engineering-based therapies. Current approaches in vascular network bioengineering are largely carried out using natural hydrogels as embedding scaffolds. However, most natural hydrogels present a poor mechanical stability and a suboptimal durability, which are critical limitations that hamper their widespread applicability. The search for improved hydrogels has become a priority in tissue engineering research. Here, the suitability of a photopolymerizable gelatin methacrylate (GelMA) hydrogel to support human progenitor cell-based formation of vascular networks is demonstrated. Using GelMA as the embedding scaffold, it is shown that 3D constructs containing human blood-derived endothelial colony-forming cells (ECFCs) and bone marrow-derived mesenchymal stem cells (MSCs) generate extensive capillary-like networks in vitro. These vascular structures contain distinct lumens that are formed by the fusion of ECFC intracellular vacuoles in a process of vascular morphogenesis. The process of vascular network formation is dependent on the presence of MSCs, which differentiate into perivascular cells occupying abluminal positions within the network. Importantly, it is shown that implantation of cell-laden GelMA hydrogels into immunodeficient mice results in a rapid formation of functional anastomoses between the bioengineered human vascular network and the mouse vasculature. Furthermore, it is shown that the degree of methacrylation of the GelMA can be used to modulate the cellular behavior and the extent of vascular network formation both in vitro and in vivo. These data suggest that GelMA hydrogels can be used for biomedical applications that require the formation of microvascular networks, including the development of complex engineered tissues.     

A multistage discriminative model for tumor and lymph node detection in thoracic images

Analysis of primary lung tumors and disease in regional lymph nodes is important for lung cancer staging, and an automated system that can detect both types of abnormalities will be helpful for clinical routine. In this paper, we present a new method to automatically detect both tumors and abnormal lymph nodes simultaneously from positron emission tomography-computed tomography thoracic images. We perform the detection in a multistage approach, by first detecting all potential abnormalities, then differentiate between tumors and lymph nodes, and finally refine the detected tumors for false positive reduction. Each stage is designed with a discriminative model based on support vector machines and conditional random fields, exploiting intensity, spatial and contextual features. The method is designed to handle a wide and complex variety of abnormal patterns found in clinical datasets, consisting of different spatial contexts of tumors and abnormal lymph nodes. We evaluated the proposed method thoroughly on clinical datasets, and encouraging results were obtained.     

585nm脉冲染料激光治疗皮肤血管性疾病所致的副作用

目的:观察585nm脉冲染料激光治疗血管性疾病所致的副作用。方法:分析500例经585nm脉冲染料激光治疗后的副反应。结果:500例接受治疗的患者中发生副反应者89例。其中色素沉着35例、色素减退12例、萎缩性瘢痕40例、增生性瘢痕2例。出现副反应与疾病种类、治疗能量无关,与治疗次数有关。结论:585nm脉冲染料激光治疗血管性疾病无连续激光治疗后所致的增生性瘢痕、持续性色素沉着等副作用,用于治疗血管性疾病是比较安全的。     

Vessel surface reconstruction with a tubular deformable model

Three-dimensional (3-D) angiographic methods are gaining acceptance for evaluation of atherosclerotic disease. However, measurement of vessel stenosis from 3-D angiographic methods can be problematic due to limited image resolution and contrast. We present a method for reconstructing vessel surfaces from 3-D angiographic methods that allows for objective measurement of vessel stenosis. The method is a deformable model that employs a tubular coordinate system. Vertex merging is incorporated into the coordinate system to maintain even vertex spacing and to avoid problems of self-intersection of the surface. The deformable model was evaluated on clinical magnetic resonance (MR) images of the carotid (n=6) and renal (n=2) arteries, on an MR image of a physical vascular phantom and on a digital vascular phantom. Only one gross error occurred for all clinical images. All reconstructed surfaces had a realistic, smooth appearance. For all segments of the physical vascular phantom, vessel radii from the surface reconstruction had an error of less than 0.2 of the average voxel dimension. Variability of manual initialization of the deformable model had negligible effect on the measurement of the degree of stenosis of the digital vascular phantom     

Estimating the 3D skeletons and transverse areas of coronary arteries from biplane angiograms

A method for estimating the three-dimensional (3D) skeletons and transverse areas of the lumens of coronary arteries from digital X-ray angiograms is described. The method is based on the use of a 3D generalized cylinder (GC) consisting of a series of 3D elliptical disks transverse to and centered on a 3D skeleton (medial axis) of the coronary arteries. The estimates of the transverse areas are based on a nonlinear least-squares-error estimation technique described by D.W. Marquardt (1963). This method exploits densitometric profiles, boundary estimates, and the orientation of the arterial skeleton in 3-space and includes an automatic artery tracking procedure. It applies an adaptive window to the densitometric profile data that are used in the parameter estimation. Preliminary experimental tests of the procedure on angiograms of in vivo human coronaries and on synthetic images yield encouraging results.     

液晶投影显示系统中的透镜阵列方式

首先对大屏幕液晶投影显示系统进行分析,并在系统设计中采用透镜阵列方法提高系统的光学性能,针对光学透镜阵列方法进行探讨研究,给出透镜阵列的设计方法和设计参数,显示系统采用双排复眼透镜,在１９０Ｗ的金属卤化物灯的情况下可达到４００ＡＮＳＩ流明的光能量输出,对比度大于１００：１,均匀性大于９０％,且显示效果良好,性能优异。     

An improved electronic colon cleansing method for detection of colonic polyps by virtual colonoscopy

Electronic colon cleansing (ECC) aims to segment the colon lumen from a patient abdominal image acquired using an oral contrast agent for colonic material tagging, so that a virtual colon model can be constructed. Virtual colonoscopy (VC) provides fly-through navigation within the colon model, looking for polyps on the inner surface in a manner analogous to that of fiber optic colonoscopy. We have built an ECC pipeline for a commercial VC navigation system. In this paper, we present an improved ECC method. It is based on a partial-volume (PV) image-segmentation framework, which is derived using the well-established statistical expectation-maximization algorithm. The presented ECC method was evaluated by both visual inspection and computer-aided detection of polyps (CADpolyp) within the cleansed colon lumens obtained using 20 patient datasets. Compared to our previous ECC pipeline, which does not sufficiently consider the PV effect, the method presented in this paper demonstrates improved polyp detection by both visual judgment and CADpolyp measure.     

血栓性血小板减少性紫癜临床分析

目的:探讨血栓性血小板减少性紫癜(TTP)患者的临床特征及治疗反应,提高对TTP的诊断及治疗水平。方法:回顾性分析29例患者的临床表现、实验室检查结果、诊治及疗效。结果:29例TTP患者,平均年龄43岁,62%(18/29)为女性。8例(27.6%)临床出现典型五联征(发热、血小板减少、微血管病性溶血性贫血、神经系统症状和肾脏损害);23(79.3%)例TTP患者表现三联征(血小板减少、微血管病性溶血性贫血、神经系统症状)。所有的患者外周血涂片可见破碎红细胞,均值为8.9%(2%-20%)。本组病例以血浆置换(PE)和血浆输注(PI)治疗为主,18例患者予以PE治疗,中位置换次数为4.5次(1-10次),9例患者予以PI治疗,PE组和PI组有效率分别为72.2%和22.2%,差异有统计学意义(P=0.0369)。结论:TTP女性多见,"三联征"为其突出临床表现,血清乳酸脱氢酶及外周血破碎红细胞计数升高对诊断具有重要参考价值。PE疗效显著优于PI,为治疗TTP的首选方法。     

用LED光源的单片式LCOS彩色投影机

介绍一种以LED作为光源的单片LCOS全彩色投影机。证实由于偏振光转换导致的光输出限制是可以克服的，就是通过LCOS面板小的工作F#和LED与偏振光回收兼容性设计，而且避免了光源光束扩展量的增加。介绍LCOS投影HDTV在光收集元件和驱动方式等方面关键技术的进展。实例采用常规LED，得到大于401m的屏幕流明光通量。     

Multiscale vascular surface model generation from medical imaging data using hierarchical features

Computational fluid dynamics (CFD) modeling of blood flow from image-based patient specific models can provide useful physiologic information for guiding clinical decision making. A novel method for the generation of image-based, 3-D, multiscale vascular surface models for CFD is presented. The method generates multiscale surfaces based on either a linear triangulated or a globally smooth nonuniform rational B-spline (NURB) representation. A robust local curvature analysis is combined with a novel global feature analysis to set mesh element size. The method is particularly useful for CFD modeling of complex vascular geometries that have a wide range of vasculature size scales, in conditions where 1) initial surface mesh density is an important consideration for balancing surface accuracy with manageable size volumetric meshes, 2) adaptive mesh refinement based on flow features makes an underlying explicit smooth surface representation desirable, and 3) semi-automated detection and trimming of a large number of inlet and outlet vessels expedites model construction.     

Targeted Venous Occlusion Using Pulsed High-Intensity Focused Ultrasound

Targeted vascular occlusion is desirable for clinical therapies such as in the treatment of esophageal and gastric varices and varicose veins. The feasibility of ultrasound-mediated endothelial damage for vascular occlusion was studied. A segment of a rabbit auricular vein was treated in vivo with low duty cycle, high peak rarefaction pressure (9 MPa) high-intensity focused ultrasound pulses in the presence of intravenously administered circulating microbubbles, followed by fibrinogen injection, which resulted in the formation of an acute occlusive intravascular thrombus. Further investigation and refinements of treatment protocols are necessary for producing durable vascular occlusion.      

Principal curves for lumen center extraction and flow channel width estimation in 3-D arterial networks: theory, algorithm, and validation

We present an energy-minimization-based framework for locating the centerline and estimating the width of tubelike objects from their structural network with a nonparametric model. The nonparametric representation promotes simple modeling of nested branches and n -way furcations, i.e., structures that abound in an arterial network, e.g., a cerebrovascular circulation. Our method is capable of extracting the entire vascular tree from an angiogram in a single execution with a proper initialization. A succinct initial model from the user with arterial network inlets, outlets, and branching points is sufficient for complex vasculature. The novel method is based upon the theory of principal curves. In this paper, theoretical extension to grayscale angiography is discussed, and an algorithm to find an arterial network as principal curves is also described. Quantitative validation on a number of simulated data sets, synthetic volumes of 19 BrainWeb vascular models, and 32 Rotterdam Coronary Artery volumes was conducted. We compared the algorithm to a state-of-the-art method and further tested it on two clinical data sets. Our algorithmic outputs-lumen centers and flow channel widths-are important to various medical and clinical applications, e.g., vasculature segmentation, registration and visualization, virtual angioscopy, and vascular atlas formation and population study.     

Reconstructing the cross sections of coronary arteries from biplane angiograms

An algorithm that reconstructs the cross sections of the lumens of coronary arteries from two mutually orthogonal X-ray projections is described. The algorithm accommodates the possibility of elliptical, crescent, or star shapes. It represents each biplane projection of a transverse slice of the arterial lumen as a binary-valued image. The single-coordinate moments of these two projection images are equal to those of the slice. Since the cross-coordinate moments of the slice are not available from the projections, an algorithm to estimate these moments based on assumptions of smoothness and connectivity is developed. Once all the missing moments are estimated, the image of the slice can be estimated by inverting these moments, using the uniqueness theorem governing the relation between an image and its moments. Preliminary tests of the algorithm on synthetic data, on hardware phantoms and on a segment of a barium-enhanced in vitro coronary artery are reported.     

A computer-aided diagnosis for locating abnormalities in bone scintigraphy by a fuzzy system with a three-step minimization approach

Bone scintigraphy is an effective method to diagnose bone diseases such as bone tumors. In the scintigraphic images, bone abnormalities are widely scattered on the whole body. Conventionally, radiologists visually check the whole-body images and find the distributed abnormalities based on their expertise. This manual process is time-consuming and it is not unusual to miss some abnormalities. In this paper, a computer-aided diagnosis (CAD) system is proposed to assist radiologists in the diagnosis of bone scintigraphy. The system will provide warning marks and abnormal scores on some locations of the images to direct radiologists' attention toward these locations. A fuzzy system called characteristic-point-based fuzzy inference system (CPFIS) is employed to implement the diagnosis system and three minimizations are used to systematically train the CPFIS. Asymmetry and brightness are chosen as the two inputs to the CPFIS according to radiologists' knowledge. The resulting CAD system is of a small-sized rule base such that the resulting fuzzy rules can be not only easily understood by radiologists, but also matched to and compared with their expert knowledge. The prototype CAD system was tested on 82 abnormal images and 27 normal images. We employed free-response receiver operating characteristics method with the mean number of false positives (FPs) and the sensitivity as performance indexes to evaluate the proposed system. The sensitivity is 91.5% (227 of 248) and the mean number of FPs is 37.3 per image. The high sensitivity and moderate numbers of FP marks per image shows that the proposed method can provide an effective second-reader information to radiologists in the diagnosis of bone scintigraphy.     

Long bone panoramas from fluoroscopic X-ray images

This paper presents a new method for creating a single panoramic image of a long bone from several individual fluoroscopic X-ray images. Panoramic images are useful preoperatively for diagnosis, and intraoperatively for long bone fragment alignment, for making anatomical measurements, and for documenting surgical outcomes. Our method composes individual overlapping images into an undistorted panoramic view that is the equivalent of a single X-ray image with a wide field of view. The correlations between the images are established from the graduations of a radiolucent ruler imaged alongside the long bone. Unlike existing methods, ours uses readily available hardware, requires a simple image acquisition protocol with minimal user input, and works with existing fluoroscopic C-arm units without modifications. It is robust and accurate, producing panoramas whose quality and spatial resolution is comparable to that of the individual images. The method has been successfully tested on in vitro and clinical cases.     

Intrathoracic airway trees: segmentation and airway morphology analysis from low-dose CT scans

The segmentation of the human airway tree from volumetric computed tomography (CT) images builds an important step for many clinical applications and for physiological studies. Previously proposed algorithms suffer from one or several problems: leaking into the surrounding lung parenchyma, the need for the user to manually adjust parameters, excessive runtime. Low-dose CT scans are increasingly utilized in lung screening studies, but segmenting them with traditional airway segmentation algorithms often yields less than satisfying results. In this paper, a new airway segmentation method based on fuzzy connectivity is presented. Small adaptive regions of interest are used that follow the airway branches as they are segmented. This has several advantages. It makes it possible to detect leaks early and avoid them, the segmentation algorithm can automatically adapt to changing image parameters, and the computing time is kept within moderate values. The new method is robust in the sense that it works on various types of scans (low-dose and regular dose, normal subjects and diseased subjects) without the need for the user to manually adjust any parameters. Comparison with a commonly used region-grow segmentation algorithm shows that the newly proposed method retrieves a significantly higher count of airway branches. A method that conducts accurate cross-sectional airway measurements on airways is presented as an additional processing step. Measurements are conducted in the original gray-level volume. Validation on a phantom shows that subvoxel accuracy is achieved for all airway sizes and airway orientations.     

Photoacoustic Therapy for Precise Eradication of Glioblastoma with a Tumor Site Blood–Brain Barrier Permeability Upregulating Nanoparticle

Glioblastoma is an extremely difficult clinical indication with very few therapeutic choices. In this study, a nanoparticle is constructed featuring high red absorbance and selective penetration of the blood–brain barrier (BBB) at the tumor site. This nanoparticle can provide timely activation of the adenosine receptor on the BBB to allow self‐passage and accumulation in the tumor. The nanoparticle converts pulsed laser energy into a shockwave via photoacoustic (PA) cavitation to achieve localized mechanical damage and thus yields a precision antitumor effect. In addition to its therapeutic function, the nanoparticle‐mediated PA process can also generate images that provide valuable information regarding tumor depth, size, and vascular morphology to inform treatment planning and monitoring. The results show that the nanoparticles can be efficiently delivered into the glioblastoma via intravenous infusion and this PA shockwave therapy can selectively destroy glioblastoma tumors with no observable side effects on normal tissue.     

An optimal nonorthogonal separation of the anisotropic Gaussian convolution filter.

We give an analytical and geometrical treatment of what it means to separate a Gaussian kernel along arbitrary axes in R(n), and we present a separation scheme that allows us to efficiently implement anisotropic Gaussian convolution filters for data of arbitrary dimensionality. Based on our previous analysis we show that this scheme is optimal with regard to the number of memory accesses and interpolation operations needed. The proposed method relies on nonorthogonal convolution axes and works completely in image space. Thus, it avoids the need for a fast Fourier transform (FFT)-subroutine. Depending on the accuracy and speed requirements, different interpolation schemes and methods to implement the one-dimensional Gaussian (finite impulse response and infinite impulse response) can be integrated. Special emphasis is put on analyzing the performance and accuracy of the new method. In particular, we show that without any special optimization of the source code, it can perform anisotropic Gaussian filtering faster than methods relying on the FFT.     

Useful lifetime analysis for high-power white LEDs

An accelerated degradation test is used to analyze the useful lifetime of high-power white light-emitting diodes (HPWLEDs) as the point at which the light output declines to 70% of the initial flux in lumens, called L₇₀ In this study, the degradation-data-driven method (DDDM), including the approximation method, the analytical method, and the two-staged method, is used to analyze the useful lifetime of HPWLEDs. A response model based on an inverse power (exponential) law under different stresses is used to predict the useful lifetime under operating conditions. However, the degradation model for each HPWLED is usually fitted to an exponential function. In order to improve the fit accuracy, we present a bi-exponential model for the degradation curve of HPWLEDs. The estimation of the model parameters are easily obtained by using the nonlinear least square method. Through numerical examples, the results show that the bi-exponential model performs better than the exponential model based on the two-staged method. The extrapolation algorithm for L₇₀ should be fitted to a bi-exponential extrapolation model and two-staged method.