基于VTK的医学图像三维可视化系统

医学图像的三维可视化可以通过可视化工具包（VTK）提供的API实现。VTK是医学图像可视化的开法工具包,它把可视化的算法封装起来,利用简单的代码生成所需图形。基于VTK的医学图像三维可视化系统阐述了如何借助VTKAPI读入二维医学图像序列、操作二维图像、重建三维图像以及进行三维图像可视化的全套方案,为临床医生的诊断、治疗提供了有益的途径。     

daime, a novel image analysis program for microbial ecology and biofilm research

Combinations of microscopy and molecular techniques to detect, identify and characterize microorganisms in environmental and medical samples are widely used in microbial ecology and biofilm research. The scope of these methods, which include fluorescence in situ hybridization (FISH) with rRNA-targeted probes, is extended by digital image analysis routines that extract from micrographs important quantitative data. Here we introduce daime (digital image analysis in microbial ecology), a new computer program integrating 2-D and 3-D image analysis and visualization functionality, which has previously not been available in a single open-source software package. For example, daime automatically finds 2-D and 3-D objects in images and confocal image stacks, and offers special functions for quantifying microbial populations and evaluating new FISH probes. A novel feature is the quantification of spatial localization patterns of microorganisms in complex samples like biofilms. In combination with '3D-FISH', which preserves the 3-D structure of samples, this stereological technique was applied in a proof of principle experiment on activated sludge and provided quantitative evidence that functionally linked ammonia and nitrite oxidizers cluster together in their habitat. This image analysis method complements recent molecular techniques for analysing structure-function relationships in microbial communities and will help to characterize symbiotic interactions among microorganisms.     

基于小波变换的医学图像编码方法

高分辨率的医学图像具有很大的信息量,影响了整个数字化的远程医疗系统的实时性,因此必须在保证不丢失关键诊断信息的前提下,对医学图像进行必要的压缩。本文提出了在给定小波基下,基于二维小波分解和重构的快速压缩方法。该方法使用了向量量化技术并采用LBG算法设计码本。实验结果证明,采用该方法可获得较高的压缩比和符合诊断要求的压缩图像。     

ImageParser: a tool for finite element generation from three-dimensional medical images

Background

The finite element method (FEM) is a powerful mathematical tool to simulate and visualize the mechanical deformation of tissues and organs during medical examinations or interventions. It is yet a challenge to build up an FEM mesh directly from a volumetric image partially because the regions (or structures) of interest (ROIs) may be irregular and fuzzy.

Methods

A software package, ImageParser, is developed to generate an FEM mesh from 3-D tomographic medical images. This software uses a semi-automatic method to detect ROIs from the context of image including neighboring tissues and organs, completes segmentation of different tissues, and meshes the organ into elements.

Results

The ImageParser is shown to build up an FEM model for simulating the mechanical responses of the breast based on 3-D CT images. The breast is compressed by two plate paddles under an overall displacement as large as 20% of the initial distance between the paddles. The strain and tangential Young's modulus distributions are specified for the biomechanical analysis of breast tissues.

Conclusion

The ImageParser can successfully exact the geometry of ROIs from a complex medical image and generate the FEM mesh with customer-defined segmentation information.

     

3-D localization of cardiac structures in real time]

Radiographic 3-D localisation enables measurements to be made that facilitate the placement of the interventional device during cardiac intervention. To enable the reader to implement the method himself, we describe the computation of 3-D coordinates, acquisition of the imaging and projection data on-line, and the accuracy that can be expected with the method. The 3-D coordinates of a cardiac structure are calculated from the image point coordinates, the projection data and the system constants of a biplane isocentric X-ray unit. Technical imaging errors are corrected a priori. The biplane projection data of a run are acquired on-line and stored in a data base. The image pair of interest is identified automatically from the inscribed run number, and assigned to the projection data from the data base. The target image point is marked on the monitor for 3-D localisation. The accuracy of the method was determined by comparing the calculated and actual cross-sectional points of a centimetre grid imaged in biplane X-ray projections. 3-D localisation took an average of 9.8 +/- 1.2 seconds. Angles and distances were assessed with a standard error of 1.1 degrees and 0.8 mm. The run number is identified correctly in 98.5% of the cases. The mean absolute location error for all points and image pairs was 0.61 +/- 0.32 mm. The accuracy and precision was 0.03 +/- 0.40 mm. Radiographic 3-D localisation can be performed readily and accurately on-line. The results obtained with the method enable interventional decisions to be optimized.     

A statistical approach to computer processing of cryo-electron microscope images: virion classification and 3-D reconstruction

The scattering density of the virus is represented as a truncated weighted sum of orthonormal basis functions in spherical coordinates, where the angular dependence of each basis function has icosahedral symmetry. A statistical model of the image formation process is proposed and the maximum likelihood estimation method computed by an expectation-maximization algorithm is used to estimate the weights in the sum and thereby compute a 3-D reconstruction of the virus particle. If multiple types of virus particle are represented in the boxed images then multiple 3-D reconstructions are computed simultaneously without first requiring that the type of particle shown in each boxed image be determined. Examples of the procedure are described for viruses with known structure: (1). 3-D reconstruction of Flockhouse Virus from experimental images, (2). 3-D reconstruction of the capsid of Nudaurelia Omega Capensis Virus from synthetic images, and (3). 3-D reconstruction of both the capsid and the procapsid of Nudaurelia Omega Capensis Virus from a mixture of unclassified synthetic images.     

Coordinate systems for the carpal bones of the wrist

The eight small and complexly shaped carpal bones of the wrist articulate in six degrees of freedom with each other and to some extent with the radius and the metacarpals. With the increasing number and sophistication of studies of the carpus, a standardized definition for a coordinate system for each the carpal bones would aid in the reporting and comparison of findings. This paper presents a method for defining and constructing a coordinate system specific to each of the eight carpal bones based upon the inertial properties of the bone, derived from surface models constructed from three-dimensional (3-D) medical image volumes. Surface models from both wrists of 5 male and 5 female subjects were generated from CT image volumes in two neutral wrist positions (functional and clinical). An automated algorithm found the principal inertial axes and oriented them according to preset conditions in 85% of the bones, the remaining bones were corrected manually. Six of the eight carpal bones were significantly more extended in the functional neutral position than in the clinical neutral position. Gender had no significant effect on carpal bone posture in either wrist position. Correlations between the 3-D carpal posture and the commonly used 2-D clinical radiographic carpal angles are established. 3-D coordinate systems defined by the anatomy of the carpal bone, such as the ones presented here, are necessary to completely describe 3-D changes in the posture of the carpal bones.     

Multiresolution image registration for two-dimensional gel electrophoresis

In proteomic research, two-dimensional electrophoresis (2-D) is an important tool for investigating differential patterns of qualitative and quantitative protein expression. The strength of the technique is due to its unrivalled power of being able to separate simultaneously thousands of proteins. The key to the comparison of 2-D protein profiles, however, lies in the use of a fast and robust image matching process which is essential to the subsequent quantification procedure. To satisfy the growing demand for a robust and fully automatic method of matching 2-D gel protein separation profiles, we describe in this paper a novel registration technique based on image intensity distribution rather than selected features. The method uses a multiresolution representation of the gel profiles and exploits the fact that coarse approximations to the optimal matching can be extracted efficiently from low-resolution images. This permits the removal of misalignments at different scales in a systematic manner and the strength of the new method has been confirmed by a double blind trial of 111 2-D gel pairs. The proposed method requires neither landmarks nor an a priori image alignment, and takes about five seconds for processing a typical gel pair on a standard personal computer.     

蒙特卡罗方法和三维数字人体模型在放疗计划质量保证中的应用

放射治疗的质量保证是保证放射治疗成功的有力方法。对于放疗计划的验证和评估有CT模拟机、仿体等方法,这些方法各有优缺点。文章提出了一种用人体图像数据构造仿真模型的方法,并用蒙特卡罗软件和美国“可视人项目”的数据集计算该模型在接受放射治疗时体内剂量的三维分布。由于采用人体的真实图像数据,以及蒙特卡罗方法计算粒子输运时的准确性,该方法能够得到真实的三维剂量分布。     

Cryo-electron microscope image denoising based on the geodesic distance

Background

To perform a three-dimensional (3-D) reconstruction of electron cryomicroscopy (cryo-EM) images of viruses, it is necessary to determine the similarity of image blocks of the two-dimensional (2-D) projections of the virus. The projections containing high resolution information are typically very noisy. Instead of the traditional Euler metric, this paper proposes a new method, based on the geodesic metric, to measure the similarity of blocks.

Results

Our method is a 2-D image denoising approach. A data set of 2243 cytoplasmic polyhedrosis virus (CPV) capsid particle images in different orientations was used to test the proposed method. Relative to Block-matching and three-dimensional filtering (BM3D), Stein’s unbiased risk estimator (SURE), Bayes shrink and K-means singular value decomposition (K-SVD), the experimental results show that the proposed method can achieve a peak signal-to-noise ratio (PSNR) of 45.65. The method can remove the noise from the cryo-EM image and improve the accuracy of particle picking.

Conclusions

The main contribution of the proposed model is to apply the geodesic distance to measure the similarity of image blocks. We conclude that manifold learning methods can effectively eliminate the noise of the cryo-EM image and improve the accuracy of particle picking.

     

Distributed Network,Wireless and Cloud Computing Enabled 3-D Ultrasound; a New Medical Technology Paradigm

Medical technologies are indispensable to modern medicine. However, they have become exceedingly expensive and complex and are not available to the economically disadvantaged majority of the world population in underdeveloped as well as developed parts of the world. For example, according to the World Health Organization about two thirds of the world population does not have access to medical imaging. In this paper we introduce a new medical technology paradigm centered on wireless technology and cloud computing that was designed to overcome the problems of increasing health technology costs. We demonstrate the value of the concept with an example; the design of a wireless, distributed network and central (cloud) computing enabled three-dimensional (3-D) ultrasound system. Specifically, we demonstrate the feasibility of producing a 3-D high end ultrasound scan at a central computing facility using the raw data acquired at the remote patient site with an inexpensive low end ultrasound transducer designed for 2-D, through a mobile device and wireless connection link between them. Producing high-end 3D ultrasound images with simple low-end transducers reduces the cost of imaging by orders of magnitude. It also removes the requirement of having a highly trained imaging expert at the patient site, since the need for hand-eye coordination and the ability to reconstruct a 3-D mental image from 2-D scans, which is a necessity for high quality ultrasound imaging, is eliminated. This could enable relatively untrained medical workers in developing nations to administer imaging and a more accurate diagnosis, effectively saving the lives of people.     

3-D image analysis system and megakaryocyte quantitation

A quasi-automatic computer image analysis system has been developed for 3-D reconstruction of stained serial sections and implemented on an IBAS system. Some new automatic image analysis techniques have been designed and incorporated into the system. For image segmentation, a transition region determination based thresholding method is introduced. Neither histogram calculation nor empirical parameters are needed in the automatic threshold selection. A two step 3-D reconstruction procedure--symbolic and pictorial reconstructions--is designed to improve the flexibility and the computational capability of the system. The global level registration and local level registration are separated. The former consists of establishing the relationship among a large numbers of profile pairs dispersed in adjacent sections. A pattern matching method based on pattern recognition principles is devised to exploit the information about the statistical character of mismatch caused by deformation of sections and about the relationship of nearby objects. For the latter, an equivalent elliptical approximation method based on the physical theory of the rotation of rigid bodies is proposed. The system has been used for 3-D reconstruction and quantitation of megakaryocytes in human bone marrow tissue. Features about individual 3-D megakaryocyte cell and the spatial distribution of megakaryocytes are determined. The latter is a new contribution to megakaryocyte quantitation and is not possible by using conventional stereologic techniques. These experimental results have demonstrated the ability of the system to perform quantitative analysis.     

Real space refinement of acto-myosin structures from sectioned muscle

We have adapted a real space refinement protocol originally developed for high-resolution crystallographic analysis for use in fitting atomic models of actin filaments and myosin subfragment 1 (S1) to 3-D images of thin-sectioned, plastic-embedded whole muscle. The rationale for this effort is to obtain a refinement protocol that will optimize the fit of the model to the density obtained by electron microscopy and correct for poor geometry introduced during the manual fitting of a high-resolution atomic model into a lower resolution 3-D image. The starting atomic model consisted of a rigor acto-S1 model obtained by X-ray crystallography and helical reconstruction of electron micrographs. This model was rebuilt to fit 3-D images of rigor insect flight muscle at a resolution of 7 nm obtained by electron tomography and image averaging. Our highly constrained real space refinement resulted in modest improvements in the agreement of model and reconstruction but reduced the number of conflicting atomic contacts by 70% without loss of fit to the 3-D density. The methodology seems to be well suited to the derivation of stereochemically reasonable atomic models that are consistent with experimentally determined 3-D reconstructions computed from electron micrographs.     

On the freezing and identification of lipid monolayer 2-D arrays for cryoelectron microscopy

Lipid monolayers provide a convenient vehicle for the crystallization of biological macromolecules for 3-D electron microscopy. Although numerous examples of 3-D images from 2-D protein arrays have been described from negatively stained specimens, only six structures have been done from frozen-hydrated specimens. We describe here a method that makes high quality frozen-hydrated specimens of lipid monolayer arrays for cryoelectron microscopy. The method uses holey carbon films with patterned holes for monolayer recovery, blotting and plunge freezing to produce thin aqueous films which cover >90% of the available grid area. With this method, even specimens with relatively infrequent crystals can be screened using automated data collection techniques. Though developed for microscopic examination of 2-D arrays, the method may have wider application to the preparation of single particle specimens for 3-D image reconstruction.     

A microcomputer based system for three-dimensional reconstructions from tomographic or histologic sections

The reconstructions of three-dimensional (3-D) objects from serial two-dimensional (2-D) images can contribute to the understanding of many biologic structures, from organelles to organs and tissues. The 3-D reconstruction of sections can be divided into several major tasks: image acquisition, alignment of slices, internal object definition, object reconstruction and rotation of the completed image. A fast, versatile, interactive system was devised for the reconstruction of 3-D objects from serial 2-D images using a low-cost microcomputer, original programs and commercial software. The system allows reconstruction from any serial images, e.g., electron micrographs, histologic sections or computed tomograms. A photographic image or a microscopic field is acquired into the computer memory using a video digitizer. Slices are superimposed and aligned to each other using an operator-interactive program. A contour-(edge-) finding algorithm isolates an object of interest from the background image by "subtraction" of the image from an overlaid, slightly shifted identical image. Contours for each slice are input to a reconstruction procedure, which calculates the x, y and z coordinates of every point in a slice and the thickness and number of slices. It then calculates the illumination for every point using a given point source of light and an intensity-fading coefficient. Finally, the points are represented by cubes to provide dimension and reflective surfaces. A cube of appropriate shade and color represents in 2-D the equivalent of a 3-D object; this results in a very effective 3-D image. The reconstruction is rotated by recalculating the positions of every point defining the object and rebuilding the image.(ABSTRACT TRUNCATED AT 250 WORDS)     

3-D warped discrete cosine transform for MRI image compression

Image compression is an application of data compression on digital images. Several lossy/lossless transform coding techniques are used for image compression. Discrete cosine transform (DCT) is one such widely used technique. A variation of DCT, known as warped discrete cosine transform (WDCT), is used for 2-D image compression and it is shown to perform better than the DCT at high bit-rates. We extend this concept and develop the 3-D WDCT, a transform that has not been previously investigated. We outline some of its important properties, which make it especially suitable for image compression. We then propose a complete image coding scheme for volumetric data sets based on the 3-D WDCT scheme. It is shown that the 3-D WDCT-based compression scheme performs better than a similar 3-D DCT scheme for volumetric data sets at high bit-rates.     

Computer-aided microtomography with true 3-D display in electron microscopy

A novel research system has been designed to permit three-dimensional (3-D) viewing of high resolution image data from transmission electron microscopy (TEM) and scanning electron microscopy (SEM). The system consists of front-end primary data acquisition devices, such as TEM and SEM machines, which are equipped with computer-controlled specimen tilt stages. The output from these machines is in analogue form, where a video camera attached to the TEM provides the sequential analogue image output while the SEM direct video output is utilized. A 10 MHz digitizer transforms the video image to a digital array of 512 X 512 pixel units of 8 bits deep-stored in a frame buffer. Digital images from multiple projections are reconstructed into 3-D image boxes in a dedicated computer. Attached to the computer is a powerful true 3-D display device which has hardware for graphic manipulations including tilt and rotate on any axis and for probing the image with a 3-D cursor. Data editing and automatic contouring functions are used to enhance areas of interest, and specialized software is available for measurement of numbers, distances, areas, and volumes. With proper archiving of reconstructed image sequences, a dynamic 3-D presentation is possible. The microtomography system is highly versatile and can process image data on-line or from remote sites from which data records would typically be transported on computer tape, video tape, or floppy disk.     

Patient oriented graph-based image segmentation

Despite increased image quality including medical imaging, image segmentation continues to represent a major bottleneck in practical applications due to noise and lack of contrast. In this paper, we present a new methodology to segment noisy, low contrast medical images, with a view to developing practical applications. Firstly, the contrast of the image is enhanced and then a modified graph-based method is followed. This paper has mainly two contributions: (1) a contrast enhancement stage performed by suitably utilizing the noise present in the medical data. This step is achieved through stochastic resonance theory applied in the wavelet domain and (2) a new weighting function is proposed for traditional graph-based approaches. Both qualitative (by our clinicians/radiologists) and quantitative evaluation performed on publicly available computed tomography (CT) (MICCAI 2007 Grand Challenge workshop database) and cardiac magnetic resonance (CMR) databases reflect the potential of the proposed method even in the presence of tumors/papillary muscles.     

3-d image analysis of fluorescent drug binding

Fluorescent ligands provide the means of studying receptors in whole tissues using confocal laser scanning microscopy and have advantages over antibody- or non-fluorescence-based method. Confocal microscopy provides large volumes of images to be measured. Histogram analysis of 3-D image volumes is proposed as a method of graphically displaying large amounts of volumetric image data to be quickly analyzed and compared. The fluorescent ligand BODIFY FL-prazosin (QAPB) was used in mouse aorta. Histogram analysis reports the amount of ligand-receptor binding under different conditions and the technique is sensitive enough to detect changes in receptor availability after antagonist incubation or generic manipulations. QAPB binding was concentration dependent, causing concentration-related rightward shifts in histogram. In the presence of 10 microM phenoxybenzamine (blocking agent), the QAPB (50 nM) histogram overlaps the autofluorescence curve. The histogram obtained for the 1D knockout aorta lay to the left of that control and 1B knockout aorta, indicating a reduction in 1D receptors. We have shown, for the first time, that it is possible to graphically display binding of a fluorescent drug to a biological tissue. Although our application is specific to adrenergic receptors, the general method could be applied to any volumetric, fluorescence-image-based assay.