Stroke is a leading cause of death and long-term disability. Non-invasive magnetic resonance imaging (MRI) has been widely used for the early detection of ischemic stroke and the longitudinal monitoring of novel treatment strategies. Recent advances in MRI techniques have enabled improved sensitivity and specificity to detecting ischemic brain injury and monitoring functional recovery. This rev...

parameters evaluated from black blood DCE-MRI and histological bio-markers. Table 1. ICCs of the three parameters evaluated from black blood DCE-MRI. Fig 1. An example of the produced V-V image with K in green channel and vp in red channel. The point label the lumen of aorta. The arrow points the adjacent muscle. Assessment of inflammation in a rabbit model of early atherosclerosis: reproducibi...

UNLABELLED PET/MRI is an emerging dual-modality imaging technology that requires new approaches to PET attenuation correction (AC). We assessed 2 algorithms for whole-body MRI-based AC (MRAC): a basic MR image segmentation algorithm and a method based on atlas registration and pattern recognition (AT&PR). METHODS Eleven patients each underwent a whole-body PET/CT study and a separate multibed...

Abstract—Medical images are important to help identifying different diseases, for example, Magnetic resonance imaging (MRI) can be used to investigate the brain, spinal cord, bones, joints, breasts, blood vessels, and heart. Image segmentation, in medical image analysis, is usually the first step to find out some characteristics with similar color, intensity or texture so that the diagnosis cou...

Medical image processing is the most challenging and emerging field now a day’s. In this field, detection of brain tumor from MRI brain scan has become one of the most challenging problems, due to complex structure of brain. The quantitative analysis of MRI brain tumor allows obtaining useful key indicators of disease progression. A computer aided diagnostic system has been proposed here for de...

The objective of this proposed work is to progress brain image segmentation methods for medical imaging applications, using Fuzzy based clustering segmentation approaches. The main aim is to propose a brain epileptic segmentation system suited for MRI processing using temporal filter. The resolution is to simply segment epilepsy in MRI with reproducible outcomes. Cluster analysis recognizes col...

PURPOSE To establish intraobserver and interobserver repeatability, agreement, and symmetry of corneal nerve fiber (NF) morphology in healthy subjects using in vivo corneal confocal microscopy. METHODS Nineteen subjects underwent in vivo corneal confocal microscopy (Heidelberg Retinal Tomograph III Rostock Cornea Module) at baseline and 7 days apart. Bland-Altman plots were generated to asses...

In computer vision, image segmentation is an important problem and plays vital role in medical imaging. Analysis and diagnosis of tumor in MRI brain image involves segmentation as very essential steep. It separates the region of interest objects from the background and the other objects. Several approaches are used for MRI brain tumor segmentation. Fuzzy C Means (FCM) is most widely used fuzzy ...

...............................................................................................................................1 Background and Significance ..............................................................................................2 Parkinson’s Disease ..........................................................................................................2 Exercise and PD ...

Thick-slice image acquisitions are sometimes inevitable in magnetic resonance imaging due to limitations posed by pulse sequence timing and signal-to-noise-ratio. The estimation of an isotropic high-resolution volume from thick-slice MRI scans is desired for improved image analysis and evaluation. In this article we formulate a maximum a posteriori (MAP) estimation algorithm for high-resolution...