Cerebral abnormalities in Wilson''s disease as evaluated by ultra-low-field magnetic resonance imaging and computerized image processing

The cerebral involvement of a 13-yr-old boy with Wilson's disease was serially evaluated during the first 18 mo of D-penicillamine treatment. An ultra-low-field magnetic resonance imaging (ULF MRI) system, operating at 0.02 T, with computerized image processing was used. The half-yr period prior to the clinical diagnosis was set, the patient had showed poor school performance, emotional lability, deteriorating handwriting, progressively slow, gross, and fine motor functions, and a fixed rigid smile. No overt signs of liver disease were found. With D-penicillamine treatment (1–1.5 g/d) a continuous improvement was seen. The pretreatment MRI investigation showed pronounced pathological transformation in the basal ganglia. However, changes were seen also in most other parts of the brain indicating diffuse involvement. During treatment the computerized MR images became gradually more normal. The current magnetic resonance imaging system with computerized image processing is a sensitive and simple method for evaluation of subtle parenchymal changes of the brain.     

Visualization of the internal carotid artery using MRA images

A virtual angioscopy system is implemented to visualize the inside of the internal carotid artery (ICA) for qualitative assessment of carotid artery stenosis using magnetic resonance angiography (MRA) images. The carotid artery is one of the body regions not accessible by real optical endoscopy but can be visualized with virtual endoscopy. In order to visualize the carotid artery, it is segmented using the region-growing algorithm after locating the initial seed on the presegmented binary image. The ICA is separated from the external carotid artery (ECA) using a priori knowledge of the anatomic structure after bifurcation. A fly-through path is computed based on the medial axis transform (MAT) to automatically move the virtual camera from the common carotid artery (CCA) to the ICA. Considering interactive rendering speed and usability of standard graphic hardware, the surface-rendering algorithm with the perspective projection method is used to generate an endoscopic view of the ICA. In addition, the endoscopic view with the raycasting algorithm is provided for off-line navigation of the carotid artery. Virtual angioscopy is highly recommended as a diagnostic tool for identifying the specific location of the stenosis and for analyzing the stenosis qualitatively. The virtual angioscopy system for carotid artery will benefit radiological diagnostics, medical education, surgical planning and postoperative assessment.     

Rician noise reduction in magnetic resonance images using adaptive non-local mean and guided image filtering

This paper proposes a Rician noise reduction method for magnetic resonance (MR) images. The proposed method is based on adaptive non-local mean and guided image filtering techniques. In the first phase, a guidance image is obtained from the noisy image through an adaptive non-local mean filter. Sobel operators are applied to compute the strength of edges which is further used to control the spread of the kernel in non-local mean filtering. In the second phase, the noisy and the guidance images are provided to the guided image filter as input to restore the noise-free image. The improved performance of the proposed method is investigated using the simulated and real data sets of MR images. Its performance is also compared with the previously proposed state-of-the art methods. Comparative analysis demonstrates the superiority of the proposed scheme over the existing approaches.     

Assessment of mitral regurgitation by magnetic resonance imaging

To evaluate the potential of magnetic resonance imaging (MRI) in detection and quantification of mitral regurgitation, 26 pts. with echocardiographically or angiographically documented mitral regurgitation were examined using a 0.5 Tesla superconducting magnet. In each patient a multislice-multiphase study in a sagittal-coronal double angulated projection (four-chamber view equivalent) was performed to assess left and right ventricular volumes, ejection fraction and regurgitant fraction. Additionally a blood flow sensitive cine-study (fast field echo: FFE) was done to visualize direction and area of regurgitant jet. MRI data were compared with quantitative and qualitative assessment of mitral regurgitation by angiography, 2D echocardiography, Doppler sonography and color flow mapping. Using the FFE mode MRI was able to detect the regurgitant jet as a typical signal loss within the left atrium in all patients. The ratio of regurgitant jet area/left atrium area as determined by MRI showed a correlation with a comparable ratio from color Doppler sonography of R = 0.87 (p < 0.001). There was also good agreement in semiquantitative grading of mitral regurgitation between MRI and angiography (R = 0.77, p < 0.001). The determination of left and right ventricular stroke volume allowed the calculation of the regurgitant fraction, which showed a correlation with invasively determined regurgitation fraction of R = 0.84 (p < 0.001). These data provide additional information that MRI may be useful as a noninvasive technique to detect and quantify mitral regurgitation.     

Assessment of pulmonary artery stiffness using velocity-encoding magnetic resonance imaging: evaluation of techniques

The loss of pulmonary artery (PA) compliance has significant pathophysiological effect on the right ventricle. Noninvasive and reliable assessment of PA wall stiffness would be an essential determiner of right heart load and a clinically useful factor to assess cardiovascular risk. Two MRI techniques have been proposed for assessing PA stiffness by measuring pulse wave velocity (PWV): transit time (TT) and flow area (QA). However, no data are available that compares the two techniques and evaluates their performance, especially over a wide range of PWV values or at 3.0-T, which is the purpose of the present study. Thirty-three patients with different heart conditions were imaged using optimized high-temporal resolution and high-spatial resolution velocity-encoding MRI sequences. Statistical analysis was conducted to study intermethod, interobserver and intraobserver variabilities. The PWV measurements using TT and QA techniques showed good agreement (P>0.1). The Bland-Altman analysis showed negligible differences between the two methods (mean±S.D.=0.11±0.35 m/s, correlation coefficient r=0.94). The repeated measurements showed low interobserver and intraobserver variabilities, although the S.D. of the differences was larger in the QA technique. The mean±S.D. of the TT/QA measurement differences were −0.05±0.2/0.0±0.36 m/s and 0.02±0.26/0.02±0.39 m/s for the interobserver and intraobserver differences, respectively. In conclusion, each technique has its own advantages and disadvantages. The two techniques result in similar measurements, although the QA method is more subjective due to its dependency on operator intervention.     

Effects of image processing on the noise properties of confocal images

The effects on the noise content of producing a projection from a stack of confocal images are investigated. Processing by retaining either the mean or peak pixel value is found to reduce noise, with the former giving more noise reduction. Gaussian noise, shot noise and speckle are considered. The effects of processing on the perception of the images are discussed.     

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.     

Bone marrow findings on magnetic resonance images of the knee: accentuation by fat suppression

Long TR/double spin-echo magnetic resonance images of the knee were obtained with and without the use of fat suppression techniques in seven patients with high signal intramedullary lesions. Comparison between images was performed qualitatively and quantitatively. Contrast-to-noise ratios between focal defects and surrounding fatty marrow were higher with fat suppression in all cases. The mean contrast-to-noise ratio for images obtained with fat suppression was 53.6, while for images obtained without fat suppression the mean contrast-to-noise ratio was 17.3 (p less than 0.01).     

Motion estimation of magnetic resonance cardiac images using the Wigner-Ville and hough transforms

Myocardial motion analysis and quantification is of utmost importance for analyzing contractile heart abnormalities and it can be a symptom of a coronary artery disease. A fundamental problem in processing sequences of images is the computation of the optical flow, which is an approximation of the real image motion. This paper presents a new algorithm for optical flow estimation based on a spatiotemporal-frequency (STF) approach. More specifically it relies on the computation of the Wigner-Ville distribution (WVD) and the Hough Transform (HT) of the motion sequences. The latter is a well-known line and shape detection method that is highly robust against incomplete data and noise. The rationale of using the HT in this context is that it provides a value of the displacement field from the STF representation. In addition, a probabilistic approach based on Gaussian mixtures has been implemented in order to improve the accuracy of the motion detection. Experimental results in the case of synthetic sequences are compared with an implementation of the variational technique for local and global motion estimation, where it is shown that the results are accurate and robust to noise degradations. Results obtained with real cardiac magnetic resonance images are presented. The text was submitted by the authors in English.     

Comparing anisotropic diffusion filters for the enhancement of sodium magnetic resonance images

The anisotropic diffusion (AND) filter, an image processing technique derived from physics, was applied to low-resolution sodium magnetic resonance imaging (MRI) to examine the possibilities of image enhancement by postprocessing. We compared six different variants of AND filters. Besides the qualitative good results on phantom measurements, quantitative analyses on MRI of human kidney yielded major improvements in noise reduction and other quality measures: the noise (i.e., the standard deviation in the image background) could be reduced to 1%-2% of its original value, while linear filters (Gaussian, Fermi, Hamming) achieved a reduction to 42%-64%. Besides that, less than 5% of structures and intensities are lost when using AND filters. Comparing the different variants, the two-dimensional and the three-dimensional AND filter outperformed the histogram-of-gradient and tensor-based AND filter. We envision that by using these AND filters, quantitative analysis of sodium MRI of kidney could be improved.     

Simulation of mid-air images using combination of physically based rendering and image processing

Optical Review - Although it is beneficial to use an optical simulator to design a mid-air imaging system, the use of a simulator requires optical knowledge, and it cannot be handled by...     

Unbiased segmentation of diffusion-weighted magnetic resonance images of the brain using iterative clustering

Segmentation of diffusion-weighted echo-planar imaging (DW-EPI) is challenging because of concerns regarding spatial resolution and distortion. Methods commonly used require manual input and often need thresholding measures to segment white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF). This may introduce operator bias and misclassification error. When comparing patients with a diffuse disease process-such as multiple sclerosis (MS)--with healthy controls, although information from all images may be biased due to disease effect, this is more so if the data set employed to perform segmentation is also used as a measured outcome for the study, for example, fractional anisotropy maps. Presented in this work is an unbiased method for segmenting DW-EPI data sets using the b=0 and single-shot inversion recovery EPI into WM, GM and CSF. The method employs an iterative clustering technique to account for partial volume effects and signal variation caused by radiofrequency inhomogeneity. The technique is evaluated with both real and synthetic brain data and results compared with statistical parametric mapping (SPM02). With synthetic brain data, where a gold standard of segmentation exists, the presented method showed less misclassification compared to SPM02. The unbiased method proposed may provide a more accurate methodology of segmentation in the analysis of DWI-EPI images in conditions such as MS.