Based on an in-vitro preparation of an adult human lung combined with high-resolution tomography we developed a realistic graph representation of the bronchial tree of a particular human lung. The graph contains topological information about spatial coordinates, connectivities, diameters and branching angles of 1453 bronchi up to the 17th Horsfield order, and is characterized by asymmetric and multifractal properties. This geometrical model was the basis for the development of an unstructured, multiphase CFD model of the trachea and upper airways. This is directly relevant to research in that intricate anatomical system geometries are employed. Based on medical imaging data CFD modeling associated with complex moving geometries, multi-phase/multi-species physics, and turbulence is incorporated. We contrast this approach with the use of mass-transport equations that describe the gas transport axially. Results show that many of the transport processes within the airways depend quite sensitively on the geometry of the bronchial bifurcations and the structure of the boundaries.
KEYWORDS: Lung, Data modeling, Visual process modeling, Gases, Image segmentation, Diffusion, Systems modeling, Medical imaging, Visualization, Nitrogen
Based on clinical CT-data a patient individual model of the bronchial-tree is constructed, incorporating information on irregular dichotomic branching of the airway bifurcations. Combining this geometric model with analytical models of transport and uptake of gas a patient individual outline of ventilation of the lung and the individual time course of inhalation is given. Conjunctions to multi-breath washout analysis are deduced. Central purpose of the presented model is to assess the significance of patient individual local airway geometry on the global ventilation of the lung and the resulting uptake of inhaled gases in the gas exchange regions of the lung.
We report on development of a new type of tissue analysis that facilitates a comprehensive method to characterize tissues and simultaneously identifies significant genes, based on the combination of different statistical approaches using co-variants such as quantitative microscopical tissue data. The introduction of tissue imaging into bioinformatics relies on a computer assisted histomorphometry, which enables tissue imaging to be executed in a fully automated, high-throughput fashion with quantitative analytical capabilities. As cells and tissues are centrally located in the biological hierarchy of function, improvements in the ability to obtain more quantitative information about tissue structure are critical to elucidate upstream functional effects of gene and protein expression. Furthermore, a detailed quantitative description of tissues may be expected to improve diagnosis and the understanding of structure and function of larger tissue constructs and organs in normal and disease states. Particular methods are described
here that correlate gene expression to tissue structural data, essentially linking a bottom-up and top-down methodology important for improvement of diagnosis and discovery informatics.
Two complementary techniques for the imaging of tissue subunits are discussed. A computer guided light microscopic imaging technique is described first, which confocally resolves thick serial sections axially. The lateral area of interest is increased by scanning a mosaic of images in each plane. Subsequently, all images are fused digitally to form a highly resolved volume exhibiting the fine structure of complete respiratory units of lung. A different technique described is based on microtomography. This method allows to image volumes up to 3x3x3 cm at a resolution of up to 7 microns. Due to the lack of strong density differences, a contrast enhancement procedure is introduced which makes this technique applicable for the imaging of lung tissue. Imaging, visualization and analysis described here are parts of an ongoing project to model structure and to simulate function of tissue subunits and complete organs.
This paper discusses some aspects of standardization in digital microscopy. Included are image acquisition , use of image and
graphics formats and data protocols in multidimensions, particular image
analysis procedures and use of industry standards for software development
In time-lapse microscopy image quality is limited by instrumental and specimen characteristics. Moreover, an enormous amount of data may be accumulated. This challenges not only the development of new tools for image processing, but typically forces methods to be executed in combination. To remedy essential problems, an image processing pipeline is employed which features image restoration, image compression, visualization and analysis. To control the flow of information within this pipeline and to optimize the parameter settings like compression rates or number of iterations, the information content is evaluated on the basis of the ratio of signal and noise.
KEYWORDS: Image compression, Image quality, Databases, Visualization, Fractal analysis, Data compression, Signal to noise ratio, Data storage, Image processing, Microscopy
Image compression in microscopy is a valuable technique, in particular if applied to multidimensional data. Information- preserving and competitive information-losing compression is applied to microscopical data and the resulting image quality is evaluated on a quantitative basis both in the spatial and frequency domain. Included are image data featuring different signal-to-noise ratios, but also voxel data for volume representations as well as graphical data for surface representations. The effect of compression on 3-D visualization and image management with data bases is included.
In most operation theaters today planning is done using pre- operatively gathered data, such as CT, MRI, or ultrasound (US). This data can become useless in cases such as lesion removal in brain, where dura opening and other preparations cause tissue shifting. A possibility to greatly increase accuracy in an ongoing operation is the use of 3D ultrasonography. The sequences of intra-operatively obtained 2D US-slices can be transformed into 3D, matched to previously acquired data, and be used to adapt the surgical planning to the current situation. The matching is done after standard image processing procedures have been applied to the 2D US data, this data has been injected into a 3D data cube, segmentation, and topological differentiation have taken place. This requires the usage of highly sophisticated graphics workstations. The objective is to create a framework in which surgeons and/or robotic neuronavigators can be informed and guided with the newest and most precise information possible during an operation.
KEYWORDS: Mathematical modeling, Computer simulations, Lung, 3D modeling, Visualization, Process modeling, Systems modeling, Data modeling, 3D acquisition, Convection
This paper discusses some aspects of computer based modeling of biological microstructures. The workflow tom model and simulate a biological structure is described as a feedback- loop. Beside the system definition by structural and dynamical properties, the simulation is discussed as a mathematical representation coupled with a computer visualization. As an example, the investigation of the functional behavior of lung structures is described with special emphasis to the modeling of respiratory units.
A framework for a computer-guided image acquisition procedure in confocal microscopy is described, which allows a 9-fold increase of the field of view and an extended imaging in axial direction by scanning aligned thick serial sections. Using an image compositing technique, complete respiratory units (acini) of small mammalian species (rat, mouse) could be investigated at high resolution. The quantification of the composed volume includes segmentation and topological investigation. With the help of parameters measured, a computer model of the acinus is designed to prepare functional simulations. In order to study flow of air in the acini, diffusion and the oxygen uptake, a set of mass transport equations is solved iteratively. The structural dynamics of ventilatory units during inhalation and expiration is also included.
The essence of scientific visualization is captured in microscopy. Microscopy systems are a proven valuable tool for biomedical research. Most of our present knowledge of structural organization in living organisms from the cellular to the molecular level is imprinted by microscopical findings. This tutorial provided an introduction into modem forms of 3-D microscopy (e.g., confocal, NMR, X-ray), and covered image quality considerations, microscopy setup, and computational considerations. Deconvolution techniques, image preprocessing, segmentation methods and various forms of 3-D rendering were reviewed. The effects of specimen preparation and image contrast on visualization were discussed. The use of stereo-imaging and virtual reality applications in modem 3-D microscopy was presented.
This paper discusses how digital image quality criteria help to optimize image quality, in particular for applications in laser scanning microscopy. Image quality considerations offer a uniform description of the available transfer characteristics, which are summed up and weighted properly to finally represent the system by a single number. In the spatial domain we can measure sharpness and contrast of the (digital) volumes by analyzing intensities and their local dependencies in a statistical fashion. This includes sum modulus difference, gray level variance, and lateral inhibition. Based on information theory, the criterion volume fidelity takes into account the knowledge of the spatial structure of a test object and compares the intensities with those present in the final digital image. Applications presented here include measurement of image quality improvement when going from non-confocal to confocal imaging, testing of new confocal system designs and the evaluation of digital post-processing methods. Limitations in the presence of noise are discussed.
Computer representation in biological microscopy is progressing from the well established modeling of three-dimensional (3-D) structural information towards the visualization of spatio- temporal (4-D) information. This paper describes two new methods to process sequential volumes, where each data set corresponds to a time sample. The first technique is based on surface rendering to study organ and tissue development. Contour stacks are rendered and in- between stages are interpolated. This technique allows the analysis and simulation of growth following different mathematical models and relates them with experimental findings. The second technique got appreciation for volume rendering of morphogenesis in living tissue. Sequences scanned with a confocal microscope are packed. The combination of ray-casting reconstructions within a color model allows for a rendering of morphogenetic activity.
A Zeiss laser scanning microscope was fitted with a high powered Argon ion laser (10 W) which provided wavelengths in the following regions: 364 nm (multiline), 488 nm and 514 nm. A Zeiss water object of 40X, NA. 0.6, corrected for the UV was used to measure the fluorescence from optical sections of a freshly enucleated rabbit eye. The resolution in the transverse direction was about 0.5 micron and the range resolution was about 0.7 micron at 366 nm wavelengths. The confocal microscope was used in both the reflected mode and the confocal mode to image the endothelial cells of the enucleated eye. Reflected light images were obtained at all wavelengths from the argon laser, and also from the HeNe laser line at 633 nm was used to image the cells in reflected light. The same fields of cells were imaged in fluorescence light. The wavelengths of excitation of 366 nm for the excitation and 400-500 for the emission were used to image the pyridine nucleotides. The reduced pyridine nucleotides are suitable chromophores for the evaluation of cellular hypoxia in the living eye. This paper demonstrated the feasibility of two dimensional fluorescent imaging of the reduced pyridine nucleotides in the corneal endothelial cells. The confocal image was made through 400 microns of corneal tissue.
This review gives an inventory of methodologies used in three-dimensional imaging and visualization in biomedical sciences. It mainly addresses multislice data acquisition in microscopy and clinical scanners. Subjects treated for visual ization of volume data sets are three-dimensional reconstruction representation editing animation techniques and special hardware solutions. 1
KEYWORDS: 3D image processing, 3D displays, 3D acquisition, 3D image reconstruction, Image processing, Confocal microscopy, Image acquisition, Microscopy, Tissue optics, Medical imaging
In this study we describe three different approaches for the 3-D reconstruction of the spatial arrangement of iniranuclear chromatin. Using a Zeiss confocal laser scanning microscope (CLSM) image acquisition of optical sections was achieved in the fluorescence mode either using isolated nuclei stained with ethidiumbromide (EthBr) or on Feulgen stained tissue whole mounts. Different methods were applied for 3-D reconstruction: (i) contours of interesting structures were outlined by interactive cursor movement on a digitizer tablet (ii) digitized optical sections were transformed into image stacks by a software implemented on the microscope system and finally processed for a 3-D display and (iii) a ray-tracing method was used to provide a 3-D display of reconstructed surfaces from serial CLSM images after extensive image preprocessing. The characteristics of the different methods are discussed with respect to the biological system used.
Optical Technologies to Solve Problems in Tissue Engineering and Tissue Mechanics
25 January 2003 | San Jose, CA, United States
Laser Tissue Interaction XIII
21 January 2002 | San Jose, CA, United States
Optical Technologies to Solve Problems in Tissue Engineering
20 January 2002 | San Jose, CA, United States
Course Instructor
SC045: Multidimensional Image Processing in Modern Microscopy
Image processing in modern microscopy is the key issue to generate insight into the 3 and 4-dimensional nature of biological specimens. This course will review the complementary methods which have been developed to render, display and store multi-dimensional images. The relation between the image quality achieved by the imaging apparatus, the appropriate methods for image enhancement and the subsequent analyzing procedures will be highlighted. A topic on its own is the functional simulation of microstructures based on microscopical data. A brief evaluation of current image processing packages and databases available on the market will be included.
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