MRS glucose mapping and PET joining forces: re-evaluation of the lumped constant in the rat brain under isoflurane anaesthesia.

Although numerous positron emission tomography (PET) studies with (18) F-fluoro-deoxyglucose (FDG) have reported quantitative results on cerebral glucose kinetics and consumption, there is a large variation between the absolute values found in the literature. One of the underlying causes is the inconsistent use of the lumped constants (LCs), the derivation of which is often based on multiple assumptions that render absolute numbers imprecise and errors hard to quantify. We combined a kinetic FDG-PET study with magnetic resonance spectroscopic imaging (MRSI) of glucose dynamics in Sprague-Dawley rats to obtain a more comprehensive view of brain glucose kinetics and determine a reliable value for the LC under isoflurane anaesthesia. Maps of Tmax /CMRglc derived from MRSI data and Tmax determined from PET kinetic modelling allowed to obtain an LC-independent CMRglc . The LC was estimated to range from 0.33 ± 0.07 in retrosplenial cortex to 0.44 ± 0.05 in hippocampus, yielding CMRglc between 62 ± 14 and 54 ± 11 μmol/min/100 g, respectively. These newly determined LCs for four distinct areas in the rat brain under isoflurane anaesthesia provide means of comparing the growing amount of FDG-PET data available from translational studies.

The use of the SeDeM diagram expert system for the formulation of Captopril SR matrix tablets by direct compression

The SeDeM Diagram Expert System has been used to study excipients, Captopril and designed formulations for their galenic characterization and to ascertain the critical points of the formula affecting product quality to obtain suitable formulations of Captopril Direct Compression SR Matrix Tablets. The application of the Sedem Diagram Expert System enables selecting excipients with in order to optimize the formula in the preformulation and formulation studies. The methodology is based on the implementation of ICH Q8, establishing the design space of the formula with the use of experiment design, using the parameters of the SeDeM Diagram Expert System as system responses.

Effect of compression wood on surface roughness and surface absorption of medium density fiberboard

Abstract

Dissecting the compression of mortality in Switzerland, 1876-2005

This paper aims to examine changes in common longevity and variability of the adult life span, and attempts to answer whether or not the compression of mortality continues in Switzerland in the years 1876-2005. The results show that the negative relationships between the large increase in the adult modal age at death, observed at least from the 1920s, and the decrease in the standard deviation of the ages at deaths occurring above it, illustrate a significant compression of adult mortality. Typical adult longevity increased by about 10% during the last fifty years in Switzerland, and adult heterogeneity in the age at death decreased in the same proportion. This analysis has not found any evidence suggesting that we are approaching longevity limits in term of modal or even maximum life spans. It ascertains a slowdown in the reduction of adult heterogeneity in longevity, already observed in Japan and other low mortality countries.

Comparison of an EMG-based and a stress-based method to predict shoulder muscle forces.

The estimation of muscle forces in musculoskeletal shoulder models is still controversial. Two different methods are widely used to solve the indeterminacy of the system: electromyography (EMG)-based methods and stress-based methods. The goal of this work was to evaluate the influence of these two methods on the prediction of muscle forces, glenohumeral load and joint stability after total shoulder arthroplasty. An EMG-based and a stress-based method were implemented into the same musculoskeletal shoulder model. The model replicated the glenohumeral joint after total shoulder arthroplasty. It contained the scapula, the humerus, the joint prosthesis, the rotator cuff muscles supraspinatus, subscapularis and infraspinatus and the middle, anterior and posterior deltoid muscles. A movement of abduction was simulated in the plane of the scapula. The EMG-based method replicated muscular activity of experimentally measured EMG. The stress-based method minimised a cost function based on muscle stresses. We compared muscle forces, joint reaction force, articular contact pressure and translation of the humeral head. The stress-based method predicted a lower force of the rotator cuff muscles. This was partly counter-balanced by a higher force of the middle part of the deltoid muscle. As a consequence, the stress-based method predicted a lower joint load (16% reduced) and a higher superior-inferior translation of the humeral head (increased by 1.2 mm). The EMG-based method has the advantage of replicating the observed cocontraction of stabilising muscles of the rotator cuff. This method is, however, limited to available EMG measurements. The stress-based method has thus an advantage of flexibility, but may overestimate glenohumeral subluxation.

A robust audio watermarking scheme based on MPEG 1 Layer 3 Compression

This paper describes an audio watermarking scheme based on lossy compression. The main idea is taken from an image watermarking approach where the JPEG compression algorithm is used to determine where and how the mark should be placed. Similarly, in the audio scheme suggested in this paper, an MPEG 1 Layer 3 algorithm is chosen for compression to determine the position of the mark bits and, thus, the psychoacoustic masking of the MPEG 1 Layer 3compression is implicitly used. This methodology provides with a high robustness degree against compression attacks. The suggested scheme is also shown to succeed against most of the StirMark benchmark attacks for audio.

Patterns of neurovascular compression in patients with classic trigeminal neuralgia: A high-resolution MRI-based study.

PURPOSE: To describe the anatomical characteristics and patterns of neurovascular compression in patients suffering classic trigeminal neuralgia (CTN), using high-resolution magnetic resonance imaging (MRI). MATERIALS AND METHODS: The analysis of the anatomy of the trigeminal nerve, brain stem and the vascular structures related to this nerve was made in 100 consecutive patients treated with a Gamma Knife radiosurgery for CTN between December 1999 and September 2004. MRI studies (T1, T1 enhanced and T2-SPIR) with axial, coronal and sagital simultaneous visualization were dynamically assessed using the software GammaPlan?. Three-dimensional reconstructions were also developed in some representative cases. RESULTS: In 93 patients (93%), there were one or several vascular structures in contact, either, with the trigeminal nerve, or close to its origin in the pons. The superior cerebellar artery was involved in 71 cases (76%). Other vessels identified were the antero-inferior cerebellar artery, the basilar artery, the vertebral artery, and some venous structures. Vascular compression was found anywhere along the trigeminal nerve. The mean distance between the nerve compression and the origin of the nerve in the brainstem was 3.76±2.9mm (range 0-9.8mm). In 39 patients (42%), the vascular compression was located proximally and in 42 (45%) the compression was located distally. Nerve dislocation or distortion by the vessel was observed in 30 cases (32%). CONCLUSIONS: The findings of this study are similar to those reported in surgical and autopsy series. This non-invasive MRI-based approach could be useful for diagnostic and therapeutic decisions in CTN, and it could help to understand its pathogenesis.

Selecting Wavelet Filter for Compression of Spectra from Multispectral Images

The problem of selecting anappropriate wavelet filter is always present in signal compression based on thewavelet transform. In this report, we propose a method to select a wavelet filter from a predefined set of filters for the compression of spectra from a multispectral image. The wavelet filter selection is based on the Learning Vector Quantization (LVQ). In the training phase for the test images, the best wavelet filter for each spectrum has been found by a careful compression-decompression evaluation. Certain spectral features are used in characterizing the pixel spectra. The LVQ is used to form the best wavelet filter class for different types of spectra from multispectral images. When a new image is to be compressed, a set of spectra from that image is selected, the spectra are classified by the trained LVQand the filter associated to the largest class is selected for the compression of every spectrum from the multispectral image. The results show, that almost inevery case our method finds the most suitable wavelet filter from the pre-defined set for the compression.

Multispectral image compression using the wavelet transform

Multispectral images contain information from several spectral wavelengths and currently multispectral images are widely used in remote sensing and they are becoming more common in the field of computer vision and in industrial applications. Typically, one multispectral image in remote sensing may occupy hundreds of megabytes of disk space and several this kind of images may be received from a single measurement. This study considers the compression of multispectral images. The lossy compression is based on the wavelet transform and we compare the suitability of different waveletfilters for the compression. A method for selecting a wavelet filter for the compression and reconstruction of multispectral images is developed. The performance of the multidimensional wavelet transform based compression is compared to other compression methods like PCA, ICA, SPIHT, and DCT/JPEG. The quality of the compression and reconstruction is measured by quantitative measures like signal-to-noise ratio. In addition, we have developed a qualitative measure, which combines the information from the spatial and spectral dimensions of a multispectral image and which also accounts for the visual quality of the bands from the multispectral images.

Lossless compression of hyperspectral images

Technological progress has made a huge amount of data available at increasing spatial and spectral resolutions. Therefore, the compression of hyperspectral data is an area of active research. In somefields, the original quality of a hyperspectral image cannot be compromised andin these cases, lossless compression is mandatory. The main goal of this thesisis to provide improved methods for the lossless compression of hyperspectral images. Both prediction- and transform-based methods are studied. Two kinds of prediction based methods are being studied. In the first method the spectra of a hyperspectral image are first clustered and and an optimized linear predictor is calculated for each cluster. In the second prediction method linear prediction coefficients are not fixed but are recalculated for each pixel. A parallel implementation of the above-mentioned linear prediction method is also presented. Also,two transform-based methods are being presented. Vector Quantization (VQ) was used together with a new coding of the residual image. In addition we have developed a new back end for a compression method utilizing Principal Component Analysis (PCA) and Integer Wavelet Transform (IWT). The performance of the compressionmethods are compared to that of other compression methods. The results show that the proposed linear prediction methods outperform the previous methods. In addition, a novel fast exact nearest-neighbor search method is developed. The search method is used to speed up the Linde-Buzo-Gray (LBG) clustering method.