The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Segmentation of positron emission tomography (PET) images is an important objective because accurate measurement of signal from radio-tracer activity in a region of interest is critical for disease treatment and diagnosis. In this study, we present the use of a graph based method for providing robust, accurate, and reliable segmentation of functional volumes on PET images from standardized uptake...
Accuracy and robustness are fundamental requirements of any automated method used for segmentation of medical images. Model-based segmentation (MBS) is a well established technique, where uncertainties in image content can be to a certain extent compensated by the use of prior shape information. This approach is, however, often problematic in cases where image information does not allow for generating...
PET-CT provides aligned anatomical (CT) and functional (PET) images in a single scan, and has the potential to improve brain PET image segmentation, which can in turn improve quantitative clinical analyses. We propose a statistical segmentation algorithm that incorporates the prior anatomical knowledge represented by probabilistic brain atlas into the variational Bayes inference to delineate gray...
Automatically segmenting brain magnetic resonance images into grey matter, white matter, and cerebrospinal fluid compartments is a fundamentally important neuroimaging problem whose difficulty is heightened in the presence of aging and neurodegenerative disease. Current methods overlap greatly in terms of identifiable algorithmic components, and the impact of specific components on performance is...
The accurate left ventricular boundary detection in echocardiographic images allow cardiologists to study and assess cardiomyopathy in patients. Due to the tedious and time consuming manner of manually tracing the borders, deformable models are generally used for left ventricle segmentations. However, most deformable models require a good initialization, which is usually outlined manually by the user...
The evaluation of the carotid artery wall is fundamental for the assessment of cardiovascular risk. This paper presents the general architecture of an automatic strategy, which segments the lumen-intima and media-adventitia borders, classified under a class of Patented AtheroEdge™ systems (Global Biomedical Technologies, Inc, CA, USA). Guidelines to produce accurate and repeatable measurements of...
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...
Wireless capsule endoscopy (WCE) has been validated to be an important tool in the evaluation of gastrointestinal (GI) tract. Compared with traditional endoscope technologies, its non-invasiveness property meets with great favor of patients. However, from physician's point of view, WCE video suffers from low resolution, limited illumination, irregular movement, more importantly, imbalanced rate of...
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...
The intima-media thickness of the carotid artery (CIMT) is a validated marker of atherosclerosis. Accurate CIMT measurement can be performed by specifically designed computer algorithms. We improved a previous CIMT measurement technique by introducing a smart heuristic search for the lumen-intima (LI) and media-adventitia (MA) interfaces of the carotid distal wall. We called this new release as CARES...
Our purpose in this study is to segment the rectus abdominis muscle region in X-ray CT images, and we propose a novel recognition method based on the shape model. In this method, three steps are included in the segmentation process. The first is to generate a shape model for the rectus abdominis muscle. The second is to recognize anatomical feature points corresponding to the origin and insertion...
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...
The segmentation of three-dimensional vascular trees is an important topic in medical image processing. Although it may seem to be an easy task, many different techniques have been proposed in the literature during the last decade and many difficulties remain. One can wonder why the human eye is usually able to understand the connectivity and the topology of the different structures while most algorithms...
For any image guided surgery, independently of the technique which is used (navigation, templates, robotics), it is necessary to get a 3D bone surface model from CT or MR images. Such model is used for planning, registration and visualization. We report that graphical representation of patient bony structure and the surgical tools, interconnectively with the tracking device and patient-to-image registration...
Liver biopsy remains the gold standard in monitoring progression of liver fibrosis associated with an abnormal increase in collagen. Descriptive scoring systems are still being widely used to grade biopsy samples. In this study, we propose a new set of features by clustering collagen fibers into three groups first based on their localization and connectivity properties, and then by extracting morphological...
One can find in the literature numerous techniques to reduce noise in Magnetic Resonance Images (MRI). This paper critically reviews modern de-noising algorithms (Gaussian filter, anisotropic diffusion, wavelet, and non-local mean) in terms of their efficiency, statistical assumptions, and their ability to improve brain tumor segmentation results. We will show that although different techniques do...
We present an enhancement method based on nonlinear diffusion filter and statistical intensity approaches for smoothing and extracting 3-D vascular system from Magnetic Resonance Angiography (MRA) data. Our method distinguishes and enhances the vessels from the other embedded tissues. The Expectation Maximization (EM) technique is employed with non-linear diffusion in order to find the optimal contrast...
Geographic Atrophy (GA) of the retinal pigment epithelium (RPE) is an advanced form of atrophic age-related macular degeneration (AMD) and is responsible for about 20% of AMD-related legal blindness in the United States. Two different imaging modalities for retinas, infrared imaging and autofluorescence imaging, serve as interesting complimentary technologies for highlighting GA. In this work we explore...
In this paper, we propose a new method for the extraction of blood vessels in retinal images. This approach starts with a Hessian-based multiscale filtering method to enhance blood vessels in gray retinal images. Subsequently, a new radial symmetry transformation, which is based on line kernels, is proposed to improve the detection of vessel structures and restrain the response of nonvessel structures...
Segmenting cerebral blood vessels is of great importance in diagnostic and clinical applications, especially in quantitative diagnostics and surgery on aneurysms and arteriovenous malformations (AVM). Segmentation of CT angiography images requires algorithms robust to high intensity noise, while being able to segment low-contrast vessels. Because of this, most of the existing methods require user...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.