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 a region containing the brain tumor from 3D magnetic resonance imaging (MRI) data can help physicians to diagnose accurately the size and malignancy of the tumor. However, manual segmentation is time consuming and involves risk of having inaccurate result. In this paper, an automatic method of segmenting the region of interest (ROI), a region encompassing the brain tumor and its neighborhood,...
This work is focused on the quantitative study of Magnetic Resonance Imaging (MRI) for the purpose of identification of brain tumor by apparent diffusion coefficient (ADC) calculations of Diffusion-weighted images (DWI). Such diffusion-based measurements of cellular response can provide additional quantitative information for tissue characterization that strengthens the diagnosis carried out by conventional...
With the remarkable growth in image processing for discussing medical imaging is one of the emerging field and the requirements for advancements in medical imaging is always emergent and challenging. MRI based brain medical imaging are used for medical diagnosis since it exhibit the inner portions of the human brain and Brain tumor is the severe life altering diseases. Image segmentation plays vital...
Using neuroimaging techniques to diagnose brain tumors and detect both visible and invisible cancer cells infiltration boundaries motivated the emergence of diverse tumor segmentation algorithms. Noting the large variability in both tumor appearance and shape, the task of automatic segmentation becomes more difficult. In this paper, we propose a random-forest (RF) based learning transfer to SVM classifier...
The brain tumor segmentation studies based on MRI are attracting more and more attention in recent years due to non-invasive imaging and good soft tissue contrast. This paper describes the proposed approach for detection and extraction brain tumor from MRI scan images of brain. Asymmetry of brain is used for detection of abnormality, after detect of the tumor. The segmentation based on F-transform...
Human brain is the most complex and mysterious part of human body. Many complex functions are controlled by brain. Brain imaging is a widely applicable method for diagnosing many brain abnormalities such as brain tumor, stroke, paralysis etc. Magnetic Resonance Imaging (MRI) is one of the methods used for brain imaging. It is used for analysing internal structures in detail. Brain tumor is an abnormal...
Purpose Magnetic resonance imaging (MRI) is the pivotal diagnostic step in patients with brain tumors, and is performed before histological diagnosis is available. We hypothesized that conventional MRI is as accurate as tumor histology in differentiating malignant from benign clinical course. Methods Two neuroradiologists blinded to any clinical information evaluated the first diagnostic MRI of...
Biomedical research in last decade or so has seen the development of highly accurate algorithms focused on the detection and classification of the brain tumor into malignant or benign. As a result of these advancements a new research direction has emerged which focuses on categorizing the brain tumors based on their types, such as Glioma, Metastases, and Meningioma etc. In this paper, we present a...
This research concerned one advanced methodology for automatic localization of brain tumors that could be imaged by Magnetic Resonance Image (MRI) modality. Such methodology could be based on Iterative closest point (ICP) matching technique by using axial MRI symmetry. The idea behind this work is to compare right and left hemispheres mirrored across a central axis. Indeed a healthy brain has a strong...
Brain tumor extraction and its analysis are challenging tasks in medical image processing because brain image and its structure is complicated that can be analyzed only by expert radiologists. Segmentation plays an important role in the processing of medical images. MRI (magnetic resonance imaging) has become a particularly useful medical diagnostic tool for diagnosis of brain and other medical images...
Nowadays, medical image processing and particularly MRI images is the one of the most challenging field and emerging to help specialists in their diagnostics. In this context and to detect automatically suspicious regions or tumors, this paper presents a new approach called hybrid segmentation inspired by both mathematical morphology operators and morphological watershed segmentation. Our approach's...
Accurate automated segmentation of brain tumors in MR images is challenging due to overlapping tissue intensity distributions and amorphous tumor shape. However, a clinically viable solution providing precise quantification of tumor and edema volume would enable better pre-operative planning, treatment monitoring and drug development. Our contributions are threefold. First, we design efficient gradient...
Automatic detection of brain tumor is a difficult task due to variations in type, size, location and shape of tumors. In this paper, a multi-modality framework for automatic tumor detection is presented, fusing different Magnetic Resonance Imaging modalities including T1-weighted, T2-weighted, and T1 with gadolinium contrast agent. The intensity, shape deformation, symmetry, and texture features were...
This paper addresses the issue of the weak association between brain MRI intensity value and anatomical meaning of MR image pixels. By investigating the deformation on brain lateral ventricles and compression from tumor, the correlation between them is quantified and utilized. With the proposed feature extraction component, lateral ventricular deformation is transformed into an additional feature...
This paper addresses the issue of the weak association between brain MRI intensity value and anatomical meaning of MR image pixels. By investigating the deformation on brain lateral ventricles and compression from tumor, the correlation between them is quantified and utilized. With the proposed feature extraction component, lateral ventricular deformation is transformed into an additional feature...
The problem of automatic classification of brain images obtained by magnetic resonance imaging (MRI) is considered. In order to design the classification system, a three-stage approach is used. It consists of wavelet decomposition of the image under study, feature extraction from the LH and HL subbands using first order statistics, and final classification by support vector machines (SVM). The proposed...
The field of medical imaging gains its importance with increase in the need of automated and efficient diagnosis in a short period of time. Other than that, medical image retrieval system is to provide a tool for radiologists to retrieve the images similar to query image in content. Magnetic resonance imaging (MRI) is an imaging technique that has played an important role in neuroscience research...
This paper presents an automatic method for a repeatable, prior-based segmentation and classification of brain tumors in longitudinal MR scans. The method is designed to overcome the inter/intra observer variability and to provide a repeatable delineation of the tumor boundaries in a set of follow-up scans of the same patient. The method effectively incorporates manual delineation of the first scan...
Arterial spin labeling (ASL) allows non-invasive imaging and quantification of brain perfusion by magnetically labeling blood in the brain-feeding arteries. ASL has been used to study cerebrovascular diseases, brain tumors and neurodegenerative disorders as well as for functional imaging. The use of a perfusion template could be of great interest to study inter-subject regional variation of perfusion...
Brain tomographic techniques, such as MRI provide a plethora of pathophysiological tissue information that assists the clinician in diagnosis, therapy design/monitoring and surgery. Robust segmentation of brain tissues is a very important task in order to perform a number of computational tasks including morphological measurements of brain structures, automatic detection of asymmetries and pathologies,...
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.