From the Publisher: 
The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

Tables of integrals

Mechanical properties of the adventitia are largely determined by the organization of collagen fibers. Measurements on the waviness and orientation of collagen, particularly at the zero-stress state, are necessary to relate the structural organization of collagen to the mechanical response of the adventitia. Using the fluorescence collagen marker CNA38-OG488 and confocal laser scanning microscopy, we imaged collagen fibers in the adventitia of rabbit common carotid arteries ex vivo. The arteries were cut open along their longitudinal axes to get the zero-stress state. We used semi-manual and automatic techniques to measure parameters related to the waviness and orientation of fibers. Our results showed that the straightness parameter (defined as the ratio between the distances of endpoints of a fiber to its length) was distributed with a beta distribution (mean value 0.72, variance 0.028) and did not depend on the mean angle orientation of fibers. Local angular density distributions revealed four axially symmetric families of fibers with mean directions of 0°, 90°, 43° and −43°, with respect to the axial direction of the artery, and corresponding circular standard deviations of 40°, 47°, 37° and 37°. The distribution of local orientations was shifted to the circumferential direction when measured in arteries at the zero-load state (intact), as compared to arteries at the zero-stress state (cut-open). Information on collagen fiber waviness and orientation, such as obtained in this study, could be used to develop structural models of the adventitia, providing better means for analyzing and understanding the mechanical properties of vascular wall.

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Experimental investigation of collagen waviness and orientation in the arterial adventitia using confocal laser scanning microscopy.

https://hal.archives-ouvertes.fr/hal-01299856/document

Determination of material models for arterial walls from uniaxial extension tests and histological structure.

The goals of this paper are (i) to re-examine the constitutive law for the description of the (passive) highly nonlinear and anisotropic response of healthy elastic arteries introduced recently by the authors, (ii) to show how the mechanical response of a carotid artery under inflation and extension predicted by the structural model compares with that for a three-dimensional form of Fung-type strain-energy function, (iii) to provide a new set of material parameters that can be used in a finite element program, and (iv) to show that the model has certain mathematical features that are important from the point of view of material and numerical stability.

Comparison of a multi-layer structural model for arterial walls with a fung-type model, and issues of material stability.

A micromechanically based constitutive model for fibrous tissues is presented. The model considers the randomly crimped morphology of individual collagen fibers, a morphology typically seen in photomicrographs of tissue samples. It describes the relationship between the fiber endpoints and its arc-length in terms of a measurable quantity, which can be estimated from image data. The collective mechanical behavior of collagen fibers is presented in terms of an explicit expression for the strain-energy function, where a fiber-specific random variable is approximated by a Beta distribution. The model-related stress and elasticity tensors are provided. Two representative numerical examples are analyzed with the aim of demonstrating the peculiar mechanism of the constitutive model and quantifying the effect of parameter changes on the mechanical response. In particular, a fibrous tissue, assumed to be (nearly) incompressible, is subject to a uniaxial extension along the fiber direction, and, separately, to pure shear. It is shown that the fiber crimp model can reproduce several of the expected characteristics of fibrous tissues.

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A constitutive model for fibrous tissues considering collagen fiber crimp

Arteries are prominent organs composed of soft tissues which have to distend in response to pulse waves. Once it is possible to develop reliable mechanical models of these soft tissues, a better understanding of several cardiovascular diseases, such as atherosclerosis, and interventional treatments, such as balloon angioplasty, might be possible. Numerical simulations which are based on realistic and efficient mechanobiological models could help to find optimal medical treatment strategies against diseases and injuries. In order to obtain reliable models of blood vessels, one aim is to describe the concentration and structural arrangements of collagen fibers in the associated soft tissue. A new approach for an automatic structural analysis of collagen in the outermost layer of the human blood vessel, i.e., the adventitia (tunica externa), is proposed. The method uses light microscopic images of thinly sliced tissue samples for data extraction. Robust clustering in the RGB space and morphological operations are used to select fiber regions and mask non-fiber regions. Based on ridge and valley detections, the fiber orientations of small fiber patches are robustly calculated. Finally, region growing is used to combine the fiber patches to regions of a homogeneous fiber orientation. Experimental results demonstrate the accurate fiber orientation detection. The extracted data are intended to be used in biomechanical models for blood vessels.

Automatic analysis of collagen fiber orientation in the outermost layer of human arteries

We present a simple and universal camera calibration method. Instead of extensive setups we are exploiting the accurate angular positions of fixed stars. High precision is achieved by compensating the interfering error sources. Our approach uses a star catalog and requires a single input image only. No additional user input information such as focal length, exposure date or position is required. Fully automatic processing and fast convergence is achieved by performing three consecutive steps. First, a star segmentation and centroid finding algorithm extracts the sub-pixel positions of the luminaries. Second, an initial solution for the most essential parameters is determined by combinatorial analysis. Finally, the Levenberg-Marquardt algorithm is applied to solve the resulting non-linear system. Experimental results with several digital consumer cameras demonstrate high robustness and accuracy. The introduced method is advisable for applications where large calibration targets are required.

/pdf/camera-calibration-from-a-single-night-sky-image-3kwn4v55nq.pdf

Camera calibration from a single night sky image

Numerical simulations, which are based on reliable biomechanical models of blood vessels, can help to get a better understanding of cardiovascular diseases such as atherosclerosis, and can be used to develop optimal medical treatment strategies.The adventitia is the outer most layer of blood vessels and its mechanical properties are essentially determined by the three-dimensional, structural arrangement of collagen fibre bundles embedded in the tissue. Global information such as the orientation statistics of the fibre bundles as well as detailed information as the crimp of the single fibres within the bundles is of particular interest in biomechanical modeling.In order to obtain a sufficiently large amount of data for biomechanical modeling, a fully automatic method for the structural analysis of the soft tissue is required. In this contribution we present methods based on computer vision to fulfill this task. We start by discussing proper tissue preparation and imaging techniques that have to be used to obtain data, which reliably represents the real three-dimensional tissue structure. The next step is concerned with algorithms that robustly segment the collagen fibre bundles and cope with various kinds of artifacts. Novel segmentation techniques for robust segmentation of individual fibril bundles and methods for estimation of their parameters, such as location, shape, mean fibril orientation, crimp of fibrils, etc, is discussed. The proposed algorithms are based on novel perceptual grouping methods operating on the extracted orientation data of fibrils.Finally, we demonstrate the results obtained by our fully automatic method on real data. In addition, for a more quantitative assessment, we introduce a generative structural model that enables the synthesis of three-dimensional fibre bundles with well-defined characteristics.

Computer vision analysis of collagen fiber bundles in the adventitia of human blood vessels

Collagen fiber bundles are important constituent parts of biological soft tissues, such as tendons, blood vessels and skin. The single collagen fibers within a bundle have a certain crimp that determines the bundle's stretching characteristic, which is of particular interest in mechanobiology. A thorough understanding of the complex interrelations between mechanical factors and the associated biological responses may help to improve diagnostics, which allow disease and injury to be treated earlier. We present a method to obtain the relative stretching characteristics (RSC) of collagen (fibrous) bundles based on the analysis of microscopic tissue images. We show, how the orientation statistics of local orientations in a bundle can be directly related to the RSC. The von Mises distribution (VMD) - a circular probability distribution is used to describe the 2D orientation statistics. The k parameter of the VMD is used to obtain the mean stretching and the probability density function (PDF) of the bundles' RSC is identified.

Pierre Elbischger

Papers

A constitutive model for fibrous tissues considering collagen fiber crimp

Automatic analysis of collagen fiber orientation in the outermost layer of human arteries

Camera calibration from a single night sky image

Computer vision analysis of collagen fiber bundles in the adventitia of human blood vessels

Estimating the stretching characteristics of fiber bundles in microscopic images