92 research outputs found

    Shape localization, quantification and correspondence using Region Matching Algorithm

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    We propose a method for local, region-based matching of planar shapes, especially as those shapes that change over time. This is a problem fundamental to medical imaging, specifically the comparison over time of mammograms. The method is based on the non-emergence and non-enhancement of maxima, as well as the causality principle of integral invariant scale space. The core idea of our Region Matching Algorithm (RMA) is to divide a shape into a number of “salient” regions and then to compare all such regions for local similarity in order to quantitatively identify new growths or partial/complete occlusions. The algorithm has several advantages over commonly used methods for shape comparison of segmented regions. First, it provides improved key-point alignment for optimal shape correspondence. Second, it identifies localized changes such as new growths as well as complete/partial occlusion in corresponding regions by dividing the segmented region into sub-regions based upon the extrema that persist over a sufficient range of scales. Third, the algorithm does not depend upon the spatial locations of mammographic features and eliminates the need for registration to identify salient changes over time. Finally, the algorithm is fast to compute and requires no human intervention. We apply the method to temporal pairs of mammograms in order to detect potentially important differences between them

    Shape description and matching using integral invariants on eccentricity transformed images

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    Matching occluded and noisy shapes is a problem frequently encountered in medical image analysis and more generally in computer vision. To keep track of changes inside the breast, for example, it is important for a computer aided detection system to establish correspondences between regions of interest. Shape transformations, computed both with integral invariants (II) and with geodesic distance, yield signatures that are invariant to isometric deformations, such as bending and articulations. Integral invariants describe the boundaries of planar shapes. However, they provide no information about where a particular feature lies on the boundary with regard to the overall shape structure. Conversely, eccentricity transforms (Ecc) can match shapes by signatures of geodesic distance histograms based on information from inside the shape; but they ignore the boundary information. We describe a method that combines the boundary signature of a shape obtained from II and structural information from the Ecc to yield results that improve on them separately

    Computer image processing with application to chemical engineering

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    A literature survey covers a wide range of picture processing topics from the general problem of manipulating digitised images to the specific task of analysing the shape of objects within an image field. There follows a discussion and development of theory relating to this latter task. A number of shape analysis techniques are inapplicable or computationally untenable when applied to objects containing concavities. A method is proposed and implemented whereby any object may be divided into convex components the algebraic sum of which constitute the original. These components may be related by a tree structure. It is observed that properties based on integral measurements, e.g. area, are less susceptible to quantisation errors than those based on linear and derivative measurements such as diameters anti slopes. A set of moments invariant with respect to size, position and orientation are derived and applied to the study of the above convex components. An outline of possible further developments is given

    Shape segmentation and retrieval based on the skeleton cut space

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    3D vormverzamelingen groeien snel in veel toepassingsgebieden. Om deze effectief te kunnen gebruiken bij modelleren, simuleren, of 3D contentontwikkeling moet men 3D vormen verwerken. Voorbeelden hiervan zijn het snijden van een vorm in zijn natuurlijke onderdelen (ook bekend als segmentatie), en het vinden van vormen die lijken op een gegeven model in een grote vormverzameling (ook bekend als opvraging). Dit proefschrift presenteert nieuwe methodes voor 3D vormsegmentatie en vormopvraging die gebaseerd zijn op het zogenaamde oppervlakskelet van een 3D vorm. Hoewel allang bekend, dergelijke skeletten kunnen alleen sinds kort snel, robuust, en bijna automatisch berekend worden. Deze ontwikkelingen stellen ons in staat om oppervlakskeletten te gebruiken om vormen te karakteriseren en analyseren zodat operaties zoals segmentatie en opvraging snel en automatisch gedaan kunnen worden. We vergelijken onze nieuwe methodes met moderne methodes voor dezelfde doeleinden en laten zien dat ons aanpak kwalitatief betere resultaten kan produceren. Ten slotte presenteren wij een nieuwe methode om oppervlakskeletten te extraheren die is veel simpeler dan, en heeft vergelijkbare snelheid met, de beste technieken in zijn klasse. Samenvattend, dit proefschrift laat zien hoe men een complete workflow kan implementeren voor het segmenteren en opvragen van 3D vormen gebruik makend van oppervlakskeletten alleen

    Doctor of Philosophy

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    dissertationWhile boundary representations, such as nonuniform rational B-spline (NURBS) surfaces, have traditionally well served the needs of the modeling community, they have not seen widespread adoption among the wider engineering discipline. There is a common perception that NURBS are slow to evaluate and complex to implement. Whereas computer-aided design commonly deals with surfaces, the engineering community must deal with materials that have thickness. Traditional visualization techniques have avoided NURBS, and there has been little cross-talk between the rich spline approximation community and the larger engineering field. Recently there has been a strong desire to marry the modeling and analysis phases of the iterative design cycle, be it in car design, turbulent flow simulation around an airfoil, or lighting design. Research has demonstrated that employing a single representation throughout the cycle has key advantages. Furthermore, novel manufacturing techniques employing heterogeneous materials require the introduction of volumetric modeling representations. There is little question that fields such as scientific visualization and mechanical engineering could benefit from the powerful approximation properties of splines. In this dissertation, we remove several hurdles to the application of NURBS to problems in engineering and demonstrate how their unique properties can be leveraged to solve problems of interest

    Statistical methods for the analysis of tooth shape

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    The study of tooth shape has traditionally involved analysing distances or angles between established points of correspondence, known as landmarks. Digital imaging has aided this process, yet improved statistical techniques, which offer advantages by retaining information on the geometry of objects throughout the analysis, have so far received little attention. Since methods must be suitable for use on un-extracted teeth, a key difficulty is that unwanted variation in recorded shape results from differences in the position of patients' gingival (gum) tissue. Here we present new methodology for addressing this problem and for use in more general applications, where objects are analysed as configurations of landmarks and one would wish to account for lack of precise correspondence between certain points, in a better way than is possible using existing techniques. After introducing the ideas of Procrustes analysis to this field, we use newly proposed methods of reliability assessment to show how, in addition to failing to allow for gum variation, implementation of this technique in its standard form is problematic, due to the poor reproducibility of particular landmarks. Use of Bookstein's (1996a, d, e) semi- landmark method, which aims to overcome lack of precise correspondence along certain directions by allowing landmarks to move iteratively along chords during Procrustes registration, is investigated but found to produce unrealistic results in certain situations. Novel modifications of this method are then proposed and evaluated in terms of addressing the issues noted above. Alternatives to minimising the `bending energy' of a pair of splines mapping from the mean shape, in order to determine new semi- landmark positions are explored and two new methods, using a `nearest point' or `full Procrustes' criterion, identified as most promising. Further investigation, by application to tooth shape problems (including a simulation study of gingival tissue variation) and use on distorted configurations generated from simple geometric shapes, show that these methods offer improvements over existing techniques in terms of filtering out unwanted variation

    Three Dimensional Nonlinear Statistical Modeling Framework for Morphological Analysis

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    This dissertation describes a novel three-dimensional (3D) morphometric analysis framework for building statistical shape models and identifying shape differences between populations. This research generalizes the use of anatomical atlases on more complex anatomy as in case of irregular, flat bones, and bones with deformity and irregular bone growth. The foundations for this framework are: 1) Anatomical atlases which allow the creation of homologues anatomical models across populations; 2) Statistical representation for output models in a compact form to capture both local and global shape variation across populations; 3) Shape Analysis using automated 3D landmarking and surface matching. The proposed framework has various applications in clinical, forensic and physical anthropology fields. Extensive research has been published in peer-reviewed image processing, forensic anthropology, physical anthropology, biomedical engineering, and clinical orthopedics conferences and journals. The forthcoming discussion of existing methods for morphometric analysis, including manual and semi-automatic methods, addresses the need for automation of morphometric analysis and statistical atlases. Explanations of these existing methods for the construction of statistical shape models, including benefits and limitations of each method, provide evidence of the necessity for such a novel algorithm. A novel approach was taken to achieve accurate point correspondence in case of irregular and deformed anatomy. This was achieved using a scale space approach to detect prominent scale invariant features. These features were then matched and registered using a novel multi-scale method, utilizing both coordinate data as well as shape descriptors, followed by an overall surface deformation using a new constrained free-form deformation. Applications of output statistical atlases are discussed, including forensic applications for the skull sexing, as well as physical anthropology applications, such as asymmetry in clavicles. Clinical applications in pelvis reconstruction and studying of lumbar kinematics and studying thickness of bone and soft tissue are also discussed
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