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In this paper a new automatic skull stripping method for T1-weighted MR image of human brain is presented. Skull stripping is a process that allows to separate the brain from the rest of tissues. The proposed method is based on a 2D brain extraction making use of fuzzy c-means segmentation and morphological operators applied on transversal slices. The approach is extended to the 3D case, taking into...
We present a system to keep track of a destructive process such as a medical specimen dissection, from data acquisition to interactive and immersive visualization, in order to build ground truth models. Acquisition is a two-step process, first involving a 3D laser scanner to get a 3D surface, and then a high resolution camera for capturing the texture. This acquisition process is repeated at each...
This paper presents a study that investigated the potential of texture analysis using Fluid Sensitive Fat Suppressed MRI images for the use in detection of bone marrow edema. A total of 168 slices of knee MRI from 10 subjects were involved. Six histogram-based textures (mean intensity, standard deviation, smoothness, third moment, uniformity and entropy) were calculated in both 2D and 3D, and were...
Viability assessment of heart muscle after a myocardial infarction is an important step for diagnosis and therapy planning. It is important to quantify the area of edema because it can differentiate between viable and death myocardial tissues. In this paper an automatic method to quantify cardiac edema is presented. The method is based on a combination of morphological operations and statistical thresholding...
In patients with intractable epilepsy, focal cortical dysplasia (FCD) is the most frequent malformation of cortical development. Identification of subtle FCD lesions using brain MRI scans is very often based on the cortical thickness measurement, where brain cortex segmentation is required as a preprocessing step. However, the accuracy of the selected segmentation method can highly affect the final...
The automatic detection of longitudinal changes in brain images is valuable in the assessment of disease evolution and treatment efficacy. Most existing change detection methods that are currently used in clinical research to monitor patients suffering from neurodegenerative diseases — such as Alzheimer's — focus on large-scale brain deformations. However, such patients often have other brain impairments,...
Registration of histology to three-dimensional (3D) magnetic resonance (MR) images is often required for the analysis of brain structure and investigation of brain pathologies. A novel algorithm for deformable registration of an individual histological section to a brain MR image is described. The cost function uses a novel hybrid intensity- and boundary surface-based measure that reflects the contrast...
Three dimensional spatial selective RF pulse of practical length has been demonstrated using parallel transmission technique in Magnetic Resonance Imaging. Currently, spoke trajectory, which is a set of parallel k-space straight lines, is widely used for 3-D slab excitation to achieve sharp slice profile and a uniform or smoothly varying in-plane profile. The better control of in-plane profile mainly...
In this paper we report a method to automatically segment the internal part of globus pallidus (GPi) on the pre-operative low-resolution magnetic resonance images (MRIs) of patients affected by Parkinson's disease. Herein we used an ultra-high resolution human brain dataset as electronic atlas of reference on which we segmented the GPi. First, we registered the ultra-high resolution dataset on the...
3D Quantitative measurement of left ventricle (LV) motion on patients with acute myocardial infarction has been recognized as essential for effective LV function diagnosis. This paper presents a method to quantify 3D LV motion obtained from conventional CINE MRI using image analysis based on mathematical modeling. Level set method is employed for segmentation, and a 3D LV geometry was reconstructed...
In medical image processing segmentation of anatomical regions of the brain is the fundamental problem. Here, a brain tumor segmentation method has been developed and validated using MRI Data. In Preprocessing and Enhancement stage, medical image is converted into standard formatted image. Segmentation subdivides an image into its constituent regions or objects. This method can segment a tumor provided...
In stereopsis, excessive screen disparity is known as one of the main causes of visual fatigue. Although the visual fatigue caused by stereoscopic depth perception has been reported in a large number of subjective assessments, there has been little effort to measure objective indicators for the visual fatigue. In this study, we investigated the relationship between the visual fatigue and the amount...
This paper presents the first performance evaluation of interest points on scalar volumetric data. Such data encodes 3D shape, a fundamental property of objects. The use of another such property, texture (\ie 2D surface colouration), or appearance, for object detection, recognition and registration has been well studied, 3D shape less so. However, the increasing prevalence of depth sensors and the...
fMRI data analysis is challenging because data are generally a modest signal embedded in a high dimensional space. We present here a method for classification and discrimination among fMRI data that is based on the Self Organizing Map (SOM) algorithm. This allows no prior selection of spatial or temporal features. We applied the method to single-subject and inter-subject classification. fMRI data...
In the last few decades, image registration (IR) has been established as a very active research area in computer vision. Over the years, it has been applied to a broad range of real-world problems ranging from remote sensing to medical imaging, artificial vision, and computer-aided design. IR has been usually tackled by iterative approaches considering numerical optimization methods which are likely...
This paper presents how using a correspondence-based interpolation scheme for 3D image registration improves the registration accuracy. The interpolator takes into account correspondences across slices, which is an advantage, particularly when the volume has thick slices, and where anatomies lie non-parallel to the slice direction. We use our previously presented approach for correspondence-based...
Breast cancer is the most common non-skin cancer and the second leading cause of cancer-related death in women here in the United States. Mammography is the current standard clinical imaging modality for breast cancer screening and diagnosis, and mammographic breast density (i.e. the percentage of the entire breast volume that is taken up by dense glandular tissue) has been shown to be a biomarker...
We present a method for the registration of whole-mount digital histology images to ex vivo MR images of the prostate that relaxes the requirement for control over specimen slicing orientation. The approach uses extrinsic fiducials visible on histology and MRI, as well as block MR images of tissue slices after coarse sectioning, to support a two-stage registration approach: (1) registration of digital...
We present a method that produces data-dependent high-pass filters that can be used in, e.g., image restoration. MR volumes often suffer from bias field artifacts produced due to unsteady magnetic field and spatial variations in reception of the RF magnetic eld emitted by the subject. To cope with these artifacts, we propose a method based on the grey-weighted distance transform (GWDT). It first computes...
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