Wavelet-based characterization of vertebral trabecular bone structure from magnetic resonance images at 3 T compared with micro-computed tomographic measurements

Trabecular bone structure and bone density contribute to the strength of bone and are important in the study of osteoporosis. Wavelets are a powerful tool in characterizing and quantifying texture in an image. The purpose of this study was to validate wavelets as a tool in computing trabecular bone thickness directly from gray-level images. To this end, eight cylindrical cores of vertebral trabecular bone were imaged using 3-T magnetic resonance imaging (MRI) and micro-computed tomography (microCT). Thickness measurements of the trabecular bone from the wavelet-based analysis were compared with standard 2D structural parameters analogous to bone histomorphometry (MR images) and direct 3D distance transformation methods (microCT images). Additionally, bone volume fraction was determined using each method. The average difference in trabecular thickness between the wavelet and standard methods was less than the size of 1 pixel size for both MRI and microCT analysis. A correlation (R) of .94 for microCT measurements and that of .52 for MRI were found for the bone volume fraction. Based on these results, we conclude that wavelet-based methods deliver results comparable with those from established MR histomorphometric measurements. Because the wavelet transform is more robust with respect to image noise and operates directly on gray-level images, it could be a powerful tool for computing structural bone parameters from MR images acquired using high resolution and thus limited signal scenarios.     

Proton magnetic resonance microimaging of human trabecular bone

Proton magnetic resonance (1H magnetic resonance imaging (MRI)) images of human trabecular bone were acquired and discussed for two samples with different porosity. Three-dimensional 3D Spin Echo (3D SE) and Multi-Slice Multi-Echo (MSME) pulse sequences were examined. A very high slice resolution of (38 microm)2 was achieved (MSME). The intensity histograms were found useful for the characterization of the bone porosity. A spatial distribution of the spin-spin relaxation time T2 was monitored with the MSME pulse program. The work demonstrates the great potential of the proton MRI technique in the study of the trabecular bone morphology.     

Quantification of trabecular structure in the distal femur using magnetic resonance phase imaging

A new approach for quantifying trabecular bone tissue using the phase images of a simple gradient-echo sequence is presented. The proposed method is based on the hypothesis that the differences in susceptibility between bone and bone marrow cause magnetic field (i.e., precession phase) variations between the image voxels. Phase images of the distal femur were obtained in vivo and characterised with the use of the phase variance. Computer simulations and experimental results indicate that the distribution of the phases varies with echo time and image resolution, as expected. Keeping these fixed, however, the phase variance is found to strongly reflect variations in trabecular structure.     

Reproducibility of the quantitative assessment of cartilage morphology and trabecular bone structure with magnetic resonance imaging at 7 T

To assess the reproducibility of quantitative measurements of cartilage morphology and trabecular bone structure of the knee at 7 T, high-resolution sagittal spoiled gradient-echo images and high-resolution axial fully refocused steady-state free-precession (SSFP) images from six healthy volunteers were acquired with a 7-T scanner. The subjects were repositioned between repeated scans to test the reproducibility of the measurements. The reproducibility of each measurement was evaluated using the coefficient(s) of variation (CV). The computed CV were 1.13% and 1.55% for cartilage thickness and cartilage volume, respectively, and were 2.86%, 1.07%, 2.27% and 3.30% for apparent bone volume over total volume fraction (app.BV/TV), apparent trabecular number (app.Tb.N), apparent trabecular separation (app.Tb.Sp) and apparent trabecular thickness (app.Tb.Th), respectively. The results demonstrate that quantitative assessment of cartilage morphology and trabecular bone structure is reproducible at 7 T and motivates future musculoskeletal applications seeking the high-field strength's superior signal-to-noise ratio.     

3D reconstruction of the brain from magnetic resonance images using a connectivity algorithm

We present high resolution three dimensional (3D) connectivity, surface construction and display algorithms that detect, extract, and display the surface of a brain from contiguous magnetic resonance (MR) images. The algorithms identify the external brain surface and create a 3D image, showing the fissures and surface convolutions of the cerebral hemispheres, cerebellum, and brain stem. Images produced by these algorithms also show the morphology of other soft tissue boundaries such as the cerebral ventricular system and the skin of the patient. For the purposes of 3D reconstruction, our experiments show that T1 weighted images give better contrast between the surface of the brain and the cerebral spinal fluid than T2 weighted images. 3D reconstruction of MR data provides a non-invasive procedure for examination of the brain surface and other anatomical features.     

Detection of pseudoperiodic patterns using partial acquisition of magnetic resonance images

Improving the resolution of magnetic resonance imaging (MRI), or, alternatively, reducing the acquisition time, can be quite beneficial for many applications. The main motivation of this work is the assumption that any information that is a priori available on the target image could be used to achieve this goal. In order to demonstrate this approach, we present a novel partial acquisition strategy and reconstruction algorithm, suitable for the special case of detection of pseudoperiodic patterns. Pseudoperiodic patterns are frequently encountered in the cerebral cortex due to its columnar functional organization (best exemplified by orientation columns and ocular dominance columns of the visual cortex). We present a new MRI research methodology, in which we seek an activity pattern, and a pattern-specific experiment is devised to detect it. Such specialized experiments extend the limits of conventional MRI experiments by substantially reducing the scan time. Using the fact that pseudoperiodic patterns are localized in the Fourier domain, we present an optimality criterion for partial acquisition of the MR signal and a strategy for obtaining the optimal discrete Fourier transform (DFT) coefficients. A by-product of this strategy is an optimal linear extrapolation estimate. We also present a nonlinear spectral extrapolation algorithm, based on projections onto convex sets (POCSs), used to perform the actual reconstruction. The proposed strategy was tested and analyzed on simulated signals and in MRI phantom experiments.     

Accelerated magnetic resonance imaging using the sparsity of multi-channel coil images

Joint estimation of coil sensitivities and output image (JSENSE) is a promising approach that improves the reconstruction of parallel magnetic resonance imaging (pMRI). However, when acceleration factor increases, the signal to noise ratio (SNR) of JSENSE reconstruction decreases as quickly as that of the conventional pMRI. Although sparse constraints have been used to improve the JSENSE reconstruction in recent years, these constraints only use the sparsity of the output image, which cannot fully exploit the prior information of pMRI. In this paper, we use the sparsity of coil images, instead of the output image, to exploit more prior information for JSENSE. Numerical simulation, phantom and in vivo experiments demonstrate that the proposed method has better performance than the SparseSENSE method and the constrained JSENSE method using the sparsity of the output image only.     

Normalization of brain magnetic resonance images using histogram even-order derivative analysis

The even-ordered (2nd, 4th and 6th) derivatives of a brain MRI histogram were used to calculate a characteristic value for white matter, which was used to normalize the image intensity scale. Simulated image histograms were used to estimate the methodological error as a function of noise level, and the optimum derivative order was determined for each image type studied (T1-, T2- and density-weighted). The algorithm yielded highly reproducible results when used in conjunction with a threshold-sensitive brain segmentation algorithm. It also proved insensitive to the presence of extra-cranial tissues. This method of histogram analysis could find utility in a variety of applications that demand robust intensity normalization including image registration, brain segmentation, tissue classification and spatial inhomogeneity correction.     

Automated classification of multispectral MR images using unsupervised constrained energy minimization based on fuzzy logic

Constrained energy minimization (CEM) has proven highly effective for hyperspectral (or multispectral) target detection and classification. It requires a complete knowledge of the desired target signature in images. This work presents “Unsupervised CEM (UCEM),” a novel approach to automatically target detection and classification in multispectral magnetic resonance (MR) images. The UCEM involves two processes, namely, target generation process (TGP) and CEM. The TGP is a fuzzy-set process that generates a set of potential targets from unknown information and then applies these targets to be desired targets in CEM. Finally, two sets of images, namely, computer-generated phantom images and real MR images, are used in the experiments to evaluate the effectiveness of UCEM. Experimental results demonstrate that UCEM segments a multispectral MR image much more effectively than either Functional MRI of the Brain's (FMRIB's) automated segmentation tool or fuzzy C-means does.     

Vibration control of a structure with ATMD against earthquake using fuzzy logic controllers

In this paper, fuzzy logic and PD controllers are designed for a multi-degree-of freedom structure with active tuned mass damper (ATMD) to suppress earthquake-induced vibrations. Fuzzy logic controller (FLC) is preferred because of its robust character, superior performance and heuristic knowledge use effectively and easily in active control. A fifteen-degree-of-freedom structural system is modeled with two types of actuators. These actuators are installed on the first storey and fifteenth storey which has ATMD. The system is then subjected to Kocaeli Earthquake vibrations, which are treated as disturbances. In control, linear motors are used as the active isolators. At the end of the study, the time history of the storey displacements and accelerations, ATMD displacements, control voltages, frequency responses of the both uncontrolled and the controlled structures are presented. Performance of the designed FLC has been shown for the different loads and disturbances using ground motion of the Kobe Earthquake. The results of the simulations show a good performance by the fuzzy logic controllers for different loads and the earthquakes.     

Advances in high-resolution nuclear magnetic resonance methods in inhomogeneous magnetic fields using intermolecular multiple quantum coherences

Strong and extremely homogeneous static magnetic field is usually required for high-resolution nu-clear magnetic resonance (NMR). However, in the cases of in vivo and so on, the magnetic field inho-mogeneity owing to magnetic susceptibility variation in samples is unavoidable and hard to eliminate by conventional methods such as shimming. Recently, intermolecular multiple quantum coherences (iMQCs) have been employed to eliminate inhomogeneous broadening and obtain high-resolution NMR spectra, especially for in vivo samples. Compared to other high-resolution NMR methods, iMQC method exhibits its unique feature and advantage. It simultaneously holds information of chemical shifts, multiplet structures, coupling constants, and relative peak areas. All the information is often used to analyze and characterize molecular structures in conventional one-dimensional NMR spec-troscopy. In this work, recent technical developments including our results in this field are summarized; the high-resolution mechanism is analyzed and comparison with other methods based on interactions between spins is made; comments on the current situation and outlook on the research directions are also made.     

Automated segmentation of lateral ventricles from human and primate magnetic resonance images using cognition network technology

Automatic segmentation of different types of tissue from magnetic resonance images is of great importance for clinical and research applications, particularly large-scale and longitudinal studies of brain pathology. We developed a fully automated algorithm for the segmentation of lateral ventricles from cranial magnetic resonance images. This problem is of interest in the study of schizophrenia, dementia and other neuropsychiatric disorders. Our algorithm achieves comparable results to expert human raters. The theoretical approach, which is based on an emerging object-oriented technology that has been adapted and evaluated to process 3D data for the first time, may, in the future, be transferred to other important problems of magnetic resonance image analysis like gray/white matter segmentation.     

Bilateral filtering of magnetic resonance phase images

High-pass filtering is required for the removal of background field inhomogeneities in magnetic resonance phase images. This high-pass filtering smooths across boundaries between areas with large differences in phase. The most prominent boundary is the surface of the brain where areas with large phase values inside the brain are located close to areas outside the brain where the phase is, on average, zero. Cortical areas, which are of great interest in brain MRI, are therefore often degraded by high-pass filtering. Here, we propose the use of the bilateral filter for the high-pass filtering step. The bilateral filter is essentially a Gaussian filter that stops smoothing at boundaries. We show that the bilateral filter improves image quality at the brain's surface, without sacrificing contrast within the brain.     

Two approaches to high-resolution high-pressure nuclear magnetic resonance

High-resolution NMR measurements have been made at elevated pressures. Two separate modifications to a commercial NMR spectrometer are described; one involves a high-pressure NMR tube which rotates in the commercial NMR probe, and the other is a complete probe head containing a nonspinning high-pressure bomb. The relative advantages and disadvantages of both modifications are discussed and it is concluded that for measurements of volumes of activation, the nonspinning probe head is superior. As an example of the utility of this probe head, two determinations of volumes of activation using it are presented.     

Semi-empirical bone model for determination of trabecular structure properties from backscattered ultrasound

A novel semi-empirical scattering model of trabecular bone facilitating its characterization and allowing optimization of the interrogating pulse-echo transducer performance was developed. The model accounts for spatial density distribution of the trabeculae and includes measurement conditions such as pressure–time waveform of the probing ultrasound wave, the emitted field structure, and the transfer function and limited bandwidth of the acoustic source operating in pulse-echo mode. These measurement conditions are of importance as they modify the scattered echoes, which in turn are linked to the micro-architecture of the bone. The bone was modeled by a random distribution of long and thin cylindrical scatterers having randomly varying diameters and mechanical properties, and oriented perpendicularly to the ultrasound beam axis. To mimic clinically encountered conditions the relevant empirical data obtained at 1 MHz were input to the model. The data included pulse-echo source pressure field distribution in the focal zone and the above mentioned transfer function. With these data the model allowed frequency dependent backscattering coefficient of the simulated bone structure and its statistical properties to be determined. The results obtained indicated that the computer simulation is of particular relevance in studying scattering properties of the cancellous bone and holds promise as a tool to determine the relationship between the physical dimensions and shape of the scatterers and for monitoring of osteoporosis. The results of simulations also indicated that the new bone model proposed is well suited to mimic clinically relevant conditions. In contrast to the existing bone models, which usually assume scatterers to be randomly distributed as infinitely long identical cylinders with a cross-section much smaller than the probing ultrasound wave, the new model includes two populations of scatterers having different physical dimensions and also allows the mechanical properties of the scatterers to be varied.