Gastrointestinal tract mucosal histomorphometry and epithelial cell proliferation and apoptosis in neonatal and adult dogs

In this study, the hypothesis was tested that the size of gastrointestinal tract (GIT) mucosal components and rates of epithelial cell proliferation and apoptosis change with increasing age. The aims were to quantitatively examine GIT histomorphology and to determine mucosal epithelial cell proliferation and apoptosis rates in neonatal (<48 h old) and adult (8 to 11.5 yr old) dogs. Morphometrical analyses were performed by light microscopy with a video-based, computer-linked system. Cell proliferation and apoptosis of the GIT epithelium were evaluated by counting the number of Ki-67 and caspase-3-positive cells, respectively, using immunohistochemical methods. Thickness of mucosal, glandular, subglandular, submucosal and muscular layers, crypt depths, villus heights, and villus widths were consistently greater (P < 0.05 to P < 0.001), whereas villus height/crypt depth ratios were smaller (P < 0.001) in adult than in neonatal dogs. The number of Ki-67-positive cells in stomach, small intestine, and colon crypts, but not in villi, was consistently greater (P < 0.01) in neonatal than in adult dogs. In contrast, the number of caspase-3-positive cells in crypts of the stomach, small intestine, and colon and in villi was not significantly influenced by age. In conclusion, canine GIT mucosal morphology and epithelial cell proliferation rates, but not apoptosis rates, change markedly from birth until adulthood is reached.

Automatic extraction of femur contours from calibrated fluoroscopic images

Automatic identification and extraction of bone contours from X-ray images is an essential first step task for further medical image analysis. In this paper we propose a 3D statistical model based framework for the proximal femur contour extraction from calibrated X-ray images. The automatic initialization is solved by an estimation of Bayesian network algorithm to fit a multiple component geometrical model to the X-ray data. The contour extraction is accomplished by a non-rigid 2D/3D registration between a 3D statistical model and the X-ray images, in which bone contours are extracted by a graphical model based Bayesian inference. Preliminary experiments on clinical data sets verified its validity

Correspondence establishment in statistical modeling of shapes with arbitrary topology

Correspondence establishment is a key step in statistical shape model building. There are several automated methods for solving this problem in 3D, but they usually can only handle objects with simple topology, like that of a sphere or a disc. We propose an extension to correspondence establishment over a population based on the optimization of the minimal description length function, allowing considering objects with arbitrary topology. Instead of using a fixed structure of kernel placement on a sphere for the systematic manipulation of point landmark positions, we rely on an adaptive, hierarchical organization of surface patches. This hierarchy can be built on surfaces of arbitrary topology and the resulting patches are used as a basis for a consistent, multi-scale modification of the surfaces' parameterization, based on point distribution models. The feasibility of the approach is demonstrated on synthetic models with different topologies.

A Closed-Form, Consistent and Robust Solution to Uncalibrated Photometric Stereo Via Local Diffuse Reflectance Maxima

Images of an object under different illumination are known to provide strong cues about the object surface. A mathematical formalization of how to recover the normal map of such a surface leads to the so-called uncalibrated photometric stereo problem. In the simplest instance, this problem can be reduced to the task of identifying only three parameters: the so-called generalized bas-relief (GBR) ambiguity. The challenge is to find additional general assumptions about the object, that identify these parameters uniquely. Current approaches are not consistent, i.e., they provide different solutions when run multiple times on the same data. To address this limitation, we propose exploiting local diffuse reflectance (LDR) maxima, i.e., points in the scene where the normal vector is parallel to the illumination direction (see Fig. 1). We demonstrate several noteworthy properties of these maxima: a closed-form solution, computational efficiency and GBR consistency. An LDR maximum yields a simple closed-form solution corresponding to a semi-circle in the GBR parameters space (see Fig. 2); because as few as two diffuse maxima in different images identify a unique solution, the identification of the GBR parameters can be achieved very efficiently; finally, the algorithm is consistent as it always returns the same solution given the same data. Our algorithm is also remarkably robust: It can obtain an accurate estimate of the GBR parameters even with extremely high levels of outliers in the detected maxima (up to 80 % of the observations). The method is validated on real data and achieves state-of-the-art results.

Experimental Validation of Finite Element Analysis of Human Vertebral Collapse Under Large Compressive Strains

Osteoporosis-related vertebral fractures represent a major health problem in elderly populations. Such fractures can often only be diagnosed after a substantial deformation history of the vertebral body. Therefore, it remains a challenge for clinicians to distinguish between stable and progressive potentially harmful fractures. Accordingly, novel criteria for selection of the appropriate conservative or surgical treatment are urgently needed. Computer tomography-based finite element analysis is an increasingly accepted method to predict the quasi-static vertebral strength and to follow up this small strain property longitudinally in time. A recent development in constitutive modeling allows us to simulate strain localization and densification in trabecular bone under large compressive strains without mesh dependence. The aim of this work was to validate this recently developed constitutive model of trabecular bone for the prediction of strain localization and densification in the human vertebral body subjected to large compressive deformation. A custom-made stepwise loading device mounted in a high resolution peripheral computer tomography system was used to describe the progressive collapse of 13 human vertebrae under axial compression. Continuum finite element analyses of the 13 compression tests were realized and the zones of high volumetric strain were compared with the experiments. A fair qualitative correspondence of the strain localization zone between the experiment and finite element analysis was achieved in 9 out of 13 tests and significant correlations of the volumetric strains were obtained throughout the range of applied axial compression. Interestingly, the stepwise propagating localization zones in trabecular bone converged to the buckling locations in the cortical shell. While the adopted continuum finite element approach still suffers from several limitations, these encouraging preliminary results towardsthe prediction of extended vertebral collapse may help in assessing fracture stability in future work.

Realizing public announcements by justifications

Modal public announcement logics study how beliefs change after public announcements. However, these logics cannot express the reason for a new belief. Justification logics fill this gap since they can formally represent evidence and justifications for an agent's belief. We present OPAL(K) and JPAL(K) , two alternative justification counterparts of Gerbrandy–Groeneveld's public announcement logic PAL(K) . We show that PAL(K) is the forgetful projection of both OPAL(K) and JPAL(K) . We also establish that JPAL(K) partially realizes PAL(K) . The question whether a similar result holds for OPAL(K) is still open.

Synchronization of two independently moving cameras without feature correspondences

In this work, a method that synchronizes two video sequences is proposed. Unlike previous methods, which require the existence of correspondences between features tracked in the two sequences, and/or that the cameras are static or jointly moving, the proposed approach does not impose any of these constraints. It works when the cameras move independently, even if different features are tracked in the two sequences. The assumptions underlying the proposed strategy are that the intrinsic parameters of the cameras are known and that two rigid objects, with independent motions on the scene, are visible in both sequences. The relative motion between these objects is used as clue for the synchronization. The extrinsic parameters of the cameras are assumed to be unknown. A new synchronization algorithm for static or jointly moving cameras that see (possibly) different parts of a common rigidly moving object is also proposed. Proof-of-concept experiments that illustrate the performance of these methods are presented, as well as a comparison with a state-of-the-art approach.