An integral conservative gridding--algorithm using Hermitian curve interpolation

The problem of re-sampling spatially distributed data organized into regular or irregular grids to finer or coarser resolution is a common task in data processing. This procedure is known as 'gridding' or 're-binning'. Depending on the quantity the data represents, the gridding-algorithm has to meet different requirements. For example, histogrammed physical quantities such as mass or energy have to be re-binned in order to conserve the overall integral. Moreover, if the quantity is positive definite, negative sampling values should be avoided. The gridding process requires a re-distribution of the original data set to a user-requested grid according to a distribution function. The distribution function can be determined on the basis of the given data by interpolation methods. In general, accurate interpolation with respect to multiple boundary conditions of heavily fluctuating data requires polynomial interpolation functions of second or even higher order. However, this may result in unrealistic deviations (overshoots or undershoots) of the interpolation function from the data. Accordingly, the re-sampled data may overestimate or underestimate the given data by a significant amount. The gridding-algorithm presented in this work was developed in order to overcome these problems. Instead of a straightforward interpolation of the given data using high-order polynomials, a parametrized Hermitian interpolation curve was used to approximate the integrated data set. A single parameter is determined by which the user can control the behavior of the interpolation function, i.e. the amount of overshoot and undershoot. Furthermore, it is shown how the algorithm can be extended to multidimensional grids. The algorithm was compared to commonly used gridding-algorithms using linear and cubic interpolation functions. It is shown that such interpolation functions may overestimate or underestimate the source data by about 10-20%, while the new algorithm can be tuned to significantly reduce these interpolation errors. The accuracy of the new algorithm was tested on a series of x-ray CT-images (head and neck, lung, pelvis). The new algorithm significantly improves the accuracy of the sampled images in terms of the mean square error and a quality index introduced by Wang and Bovik (2002 IEEE Signal Process. Lett. 9 81-4).

Influence of examiner's clinical experience on the reproducibility and accuracy of radiographic examination in detecting occlusal caries

The aim of this in vitro study was to assess the influence of varying examiner's clinical experience on the reproducibility and accuracy of radiographic examination for occlusal caries detection. Standardized bitewing radiographs were obtained from 166 permanent molars. Radiographic examination was performed by final-year dental students from two universities (A, n = 5; B, n = 5) and by dentists with 5 to 7 years of experience who work in two different countries (C, n = 5; D, n = 5). All examinations were repeated after 1-week interval. The teeth were histologically prepared and assessed for caries extension. For intraexaminer reproducibility, the unweighted kappa values were: A (0.11-0.40), B (0.12-0.33), C (0.47-0.58), and D (0.42-0.71). Interexaminer reproducibility statistics were computed based on means ± SD of unweighted kappa values: A (0.07 ± 0.05), B (0.12 ± 0.09), C (0.24 ± 0.08), and D (0.33 ± 0.10). Sensitivity, specificity, and accuracy were calculated at D(1) and D(3) thresholds and compared by performing McNemar test (p = 0.05). D(1) sensitivity ranged between 0.29 and 0.75 and specificity between 0.24 and 0.85. D(3) specificity was moderate to high (between 0.62 and 0.95) for all groups, with statistically significant difference between the dentists groups (C and D). Sensitivity was low to moderate (between 0.21 and 0.57) with statistically significant difference for groups B and D. Accuracy was similar for all groups (0.55). Spearman's correlations were: A (0.12), B (0.24), C (0.30), and D (0.38). In conclusion, the reproducibility of radiographic examination was influenced by the examiner's clinical experience, training, and dental education as well as the accuracy in detecting occlusal caries.

An accuracy approach to robotic microsurgery in the ear

Concerns of rising healthcare costs and the ever increasing desire to improve surgical outcome have motivated the development of a new robotic assisted surgical procedure for the implantation of artificial hearing devices (AHDs). This paper describes our efforts to enable minimally invasive, cost effective surgery for the implantation of AHDs. We approach this problem with a fundamental goal to reduce errors from every component of the surgical workflow from imaging and trajectory planning to patient tracking and robot development. These efforts were successful in reducing overall system error to a previously unattained level.

Diagnostic performance and accuracy of 3-D spoiled gradient-dual-echo MRI with water- and fat-signal separation in liver-fat quantification: comparison to liver biopsy

To prospectively evaluate a 3-dimensional spoiled gradient-dual-echo (3D SPGR-DE) magnetic resonance imaging (MRI) sequence for the qualitative and quantitative analysis of liver fat content (LFC) in patients with the suspicion of fatty liver disease using histopathology as the standard of reference.

Iterative Reconstruction Algorithm for Abdominal Multidetector CT at Different Tube Voltages: Assessment of Diagnostic Accuracy, Image Quality, and Radiation Dose in a Phantom Study

To assess the diagnostic accuracy, image quality, and radiation dose of an iterative reconstruction algorithm compared with a filtered back projection (FBP) algorithm for abdominal computed tomography (CT) at different tube voltages.

Accuracy of diagnostic tests for clinically suspected upper extremity deep vein thrombosis: a systematic review

The best available test for the diagnosis of upper extremity deep venous thrombosis (UEDVT) is contrast venography. The aim of this systematic review was to assess whether the diagnostic accuracy of other tests for clinically suspected UEDVT is high enough to justify their use in clinical practise and to evaluate if any test can replace venography.

Influence of Smoothing on Voxel-Based Mesh Accuracy in Micro-Finite Element

The interest in automatic volume meshing for finite element analysis (FEA) has grown more since the appearance of microfocus CT (μCT), due to its high resolution, which allows for the assessment of mechanical behaviour at a high precision. Nevertheless, the basic meshing approach of generating one hexahedron per voxel produces jagged edges. To prevent this effect, smoothing algorithms have been introduced to enhance the topology of the mesh. However, whether smoothing also improves the accuracy of voxel-based meshes in clinical applications is still under question. There is a trade-off between smoothing and quality of elements in the mesh. Distorted elements may be produced by excessive smoothing and reduce accuracy of the mesh. In the present work, influence of smoothing on the accuracy of voxel-based meshes in micro-FE was assessed. An accurate 3D model of a trabecular structure with known apparent mechanical properties was used as a reference model. Virtual CT scans of this reference model (with resolutions of 16, 32 and 64 μm) were then created and used to build voxel-based meshes of the microarchitecture. Effects of smoothing on the apparent mechanical properties of the voxel-based meshes as compared to the reference model were evaluated. Apparent Young’s moduli of the smooth voxel-based mesh were significantly closer to those of the reference model for the 16 and 32 μm resolutions. Improvements were not significant for the 64 μm, due to loss of trabecular connectivity in the model. This study shows that smoothing offers a real benefit to voxel-based meshes used in micro-FE. It might also broaden voxel-based meshing to other biomechanical domains where it was not used previously due to lack of accuracy. As an example, this work will be used in the framework of the European project ContraCancrum, which aims at providing a patient-specific simulation of tumour development in brain and lungs for oncologists. For this type of clinical application, such a fast, automatic, and accurate generation of the mesh is of great benefit.