Matching hand radiographs

Biometric verification and identification methods of medical images can be used to find possible inconsistencies in patient records. Such methods may also be useful for forensic research. In this work we present a method for identifying patients by their hand radiographs. We use active appearance model representations presented before [1] to extract 64 shape features per bone from the metacarpals, the proximal, and the middle phalanges. The number of features was reduced to 20 by applying principal component analysis. Subsequently, a likelihood ratio classifier [2] determines whether an image potentially belongs to another patient in the data set. Firstly, to study the symmetry between both hands, we use a likelihood-ratio classifier to match 45 left hand images to a database of 44 (matching) right hand images and vice versa. We found an average equal error probability of 6.4%, which indicates that both hand shapes are highly symmetrical. Therefore, to increase the number of samples per patient, the distinction between left and right hands was omitted. Secondly, we did multiple experiments with randomly selected training images from 24 patients. For several patients there were multiple image pairs available. Test sets were created by using the images of three different patients and 10 other images from patients that were in the training set. We estimated the equal error rate at 0.05%. Our experiments suggest that the shapes of the hand bones contain biometric information that can be used to identify persons

Analyzing the precision of JSW measurements using 3D scans and statistical models

One of the methods to diagnose rheumatoid arthritis (RA) is measuring joint space narrowing over time. A method is presented to analyze the sensitivity of this measurement to positioning of the hand. Micro-CT scans are used to generate projections of a joint under varying angles of rotation. A semi-automatic method is used to measure the joint space width (JSW) for each projection. A Statistical model is used to investigate whether the rotation can be detected from a 2D radiograph. It is shown that rotation of the hand has a significant influence on the measured JSW

Segmentation of Radiographs of Hands with Joint Damage Using Customized Active Appearance Models

This paper is part of a project that investigates the possibilities of automating the assessment of joint damagein hand radiographs. Our goal is to design a robust segmentationalgorithm for the hand skeleton. The algorithm is\ud based on active appearance models (AAM) [1], which have been used for hand segmentation before [2]. The results will be used in the future for radiographic assessment of rheumatoid arthritis and the early detection of joint damage. New in this work with respect to [2] is the use of multiple object warps for each individual bone in a single AAM. This method prevents modelling and reconstruction defects caused when warping overlapping objects. This makes the algorithm more robust in cases where joint damage is present. The current implementation of the model includes the metacarpals, the phalanges, and the carpal region. For a first experimental evaluation a collection of 50 hand radiographs has been gathered. The image data set was split into a training set (40) and a test set (10) in order to evaluate the algorithm’s performance. First results show that in 8 images from the test set the bone contours are detected correctly within 1.3 mm (1 STD) at 15 pixels/cm resolution. In two images not all contours are detected correctly. Possibly this is caused by extreme deviations in these images that have not yet been incorporated in the model due to a limited training set. More training examples are needed to optimize the AAM and improve the quality and reliability of the results

Grip-Pattern Recognition for Smart Guns

This paper describes the design, implementation and evaluation of a user-verification system for a smart gun, which is based on grip-pattern recognition. An existing pressure sensor consisting of an array of 44 x 44 piezoresistive elements has been used. An interface has been developed to acquire pressure images from the sensor. The values of the pixels in the pressure-pattern images are used as inputs for a verification algorithm, which is currently implemented in software on a computer. The verification algorithm is based on a likelihood-ratio classifier for Gaussian probability densities. First results indicate that it is possible to use grip-pattern recognition for biometric verification, when allowing a certain false-rejection and false-acceptance rate. However, more measurements are needed to give a more reliable indication of the systems performance

The George Washington University Budgetation, A Group Thesis Prepared by the Following Members of the 1962 Class of the Navy Graduate Financial Management Program

Were the reader to search for a definition of the term BUDGETATION in any conventional reference, the odds of his success would be indeed remote. It is a term that is offered for purposes of development as a function of Imagination, and expressed by the formula: BUDGEIATION equals BUDGET plus IMAGINATIONhttp://archive.org/details/thegeorgewashing109453879

Knotlike Cosmic Strings in The Early Universe

In this paper, the knotlike cosmic strings in the Riemann-Cartan space-time of the early universe are discussed. It has been revealed that the cosmic strings can just originate from the zero points of the complex scalar quintessence field. In these strings we mainly study the knotlike configurations. Based on the integral of Chern-Simons 3-form a topological invariant for knotlike cosmic strings is constructed, and it is shown that this invariant is just the total sum of all the self-linking and linking numbers of the knots family. Furthermore, it is also pointed out that this invariant is preserved in the branch processes during the evolution of cosmic strings

Geometric Generalization of the Nelder-Mead Algorithm

The Nelder-Mead Algorithm (NMA) is an almost half-century old method for numerical optimization, and it is a close relative of Particle Swarm Optimization (PSO) and Differential Evolution (DE). Geometric Particle Swarm Optimization (GPSO) and Geometric Differential Evolution (GDE) are recently introduced formal generalization of traditional PSO and DE that apply naturally to both continuous and combinatorial spaces. In this paper, we generalize NMA to combinatorial search spaces by naturally extending its geometric interpretation to these spaces, analogously as what was done for the traditional PSO and DE algorithms, obtaining the Geometric Nelder-Mead Algorithm (GNMA)

Joint Resummation for Higgs Production

We study the application of the joint resummation formalism to Higgs production via gluon-gluon fusion at the LHC, defining inverse transforms by analytic continuation. We work at next-to-leading logarithmic accuracy. We find that at low Q_T the resummed Higgs Q_T distributions are comparable in the joint and pure-Q_T formalisms, with relatively small influence from threshold enhancement in this range. We find a modest (about ten percent) decrease in the inclusive cross section, relative to pure threshold resummation.Comment: 22 pages, LaTeX, 5 figures as eps file