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Deformable image registration is an important tool in medical image analysis. In the case of lung computed tomography (CT) registration there are three major challenges: large motion of small features, sliding motions between organs, and changing image contrast due to compression. Recently, Markov random field (MRF)-based discrete optimization strategies have been proposed to overcome problems involved with continuous optimization for registration, in particular its susceptibility to local minima. However, to date the simplifications made to obtain tractable computational complexity reduced the registration accuracy. We address these challenges and preserve the potentially higher quality of discrete approaches with three novel contributions. First, we use an image-derived minimum spanning tree as a simplified graph structure, which copes well with the complex sliding motion and allows us to find the global optimum very efficiently. Second, a stochastic sampling approach for the similarity cost between images is introduced within a symmetric, diffeomorphic B-spline transformation model with diffusion regularization. The complexity is reduced by orders of magnitude and enables the minimization of much larger label spaces. In addition to the geometric transform labels, hyper-labels are introduced, which represent local intensity variations in this task, and allow for the direct estimation of lung ventilation. We validate the improvements in accuracy and performance on exhale-inhale CT volume pairs using a large number of expert landmarks. [ABSTRACT FROM PUBLISHER]

Positron emission tomography (PET) is a molecular imaging technique which provides important functional information about the human body. However, thoracic PET images are often substantially degraded by respiratory motion, which adversely impacts on subsequent diagnosis. In this paper, a motion correction and attenuation correction method is proposed to correct for motion in respiratory gated PET images and to yield an accurate distribution of the radioactivity concentration. Experimental results show that this method can effectively correct for motion and improve PET image quality. The method is able to provide improved diagnostic information without increasing the acquisition time or the radiation burden. [ABSTRACT FROM AUTHOR]

Textures within real images vary in brightness, contrast, scale, and skew as imaging conditions change. To enable recognition of textures in real images, it is necessary to employ a similarity measure that is invariant to these properties. Furthermore, since textures often appear on undulating surfaces, such invariances must necessarily be local rather than global. Despite these requirements, it is only relatively recently that texture recognition algorithms with local scale and affine invariance properties have begun to be reported. Typically, they comprise detecting feature points followed by geometric normalization prior to description. We describe a method based on invariant combinations of linear filters. Unlike previous methods, we introduce a novel family of filters, which provides scale invariance, resulting in a texture description invariant to local changes in orientation, contrast, and scale and robust to local skew. Significantly, the family of filters enables local scale invariants to be defined without using a scale selection principle or a large number of filters. A texture discrimination method based on the χ2 similarity measure applied to histograms derived from our filter responses outperforms existing methods for retrieval and classification results for both the Brodatz textures and the University of Illinois, Urbana-Champaign (UIUC) database, which has been designed to require local invariance. [ABSTRACT FROM AUTHOR]

In this paper, we present a two-stage algorithm for mammogram registration, the geometrical alignment of mammogram sequences. The rationale behind this paper stems from the intrinsic difficulties in comparing mammogram sequences. Mammogram comparison is a valuable tool in national breast screening programs as well as in frequent monitoring and hormone replacement therapy (HRT). The method presented in this paper aims to improve mammogram comparison by estimating the underlying geometric transformation for any mammogram sequence. It takes into consideration the various temporal changes that may occur between successive scans of the same woman and is designed to overcome the inconsistencies of mammogram image formation. [ABSTRACT FROM AUTHOR]

Develops a method for simultaneous estimation of video-intensity inhomogeities and segmentation of ultrasound image tissue regions. Information on B-Mode ultrasound imaging; Methods employed to estimate the ultrasound image distortion field; Application to clinical breast and cardiac ultrasound images.

Presents a novel model-based method for reconstructing microcalcification clusters in three-dimensions (3-D) from two mammographic views. Representation of 3-D uncompressed breast shape; Breast compression model; Matching corresponding microcalcification in different views; Validation experiments and results.

Focuses on a study which proposed a novel hidden Markov random field (HMRF) model, which is a stochastic process. Description of the HMRF model; Simulation of the model; Classification of the MRF-Maximum a posteriori; Model fitting using the expectation-maximization algorithm.

Presents enhancement algorithms for far infrared images based upon a model of an idealized far infrared image being piecewise-constant. Application of median filtering and spatial homomorphic filtering algorithms; Development of the spatiotemporal homomorphic filtering algorithm; Results of the application of the algorithms to several image sequences.

Proposes a technique for bias field estimation and segmentation of magnetic resonance (MR) images. What affects the performance of any segmentation algorithm; Information on magnetic resonance imaging (MRI); Results from the modified algorithm.

Presents a paper on mobile robots with a proposal to approach the problem of global path planning for the robots in a dynamic manufacturing environment. What is needed to model the changing environment; Identification of the elements which the cost functions consist of; Why are statistical models built built to quantify.

Discusses different sources of information regarding geostationary orbits and satellites and space travel. 'Extra-Terrestrial Relays,' an article by Arthur Charles Clarke featured in the October 1945 issue of 'Wireless World'; 'Rockets and Space Travel,' a book by Willy Ley; 'Das Problem Der Befahrung Des Weltraums,' a book by Hermann Noordung.