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APPLICATION OF VARIOUS SEGMENTATION TECHNIQUES FOR BRAIN MRI –A COMPARATIVE STUDY

by unknown authors
"... In this paper, the segmentation of magnetic resonance brain (MR) images has been analysed using K-Means clustering, Fuzzy C-Means clustering (FCM) and Pulse Coupled Neural Network (PCNN) techniques. All the three methods are applied to normal and abnormal brain MR images and the results are compared ..."
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In this paper, the segmentation of magnetic resonance brain (MR) images has been analysed using K-Means clustering, Fuzzy C-Means clustering (FCM) and Pulse Coupled Neural Network (PCNN) techniques. All the three methods are applied to normal and abnormal brain MR images and the results

Analysis and Comparison of Brain Tumor Detection and Extraction Techniques from MRI Images

by Geetika Gupta , Rupinder Kaur , Arun Bansal , Munish Bansal , 2007
"... ABSTRACT: Magnetic Resonance Imaging (MRI) is the procedure used in hospitals to scan patients and determine the severity of certain injuries. It produces high quality images of the human body part. Tumors in various body parts are also scanned using MRI. Brain tumor is an abnormal cell formation w ..."
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ABSTRACT: Magnetic Resonance Imaging (MRI) is the procedure used in hospitals to scan patients and determine the severity of certain injuries. It produces high quality images of the human body part. Tumors in various body parts are also scanned using MRI. Brain tumor is an abnormal cell formation

Measurement of brain volume using MRI: software, techniques, choices and prerequisites

by Simon S. Keller, Neil Roberts
"... Summary- Magnetic resonance imaging (MRI) permits in vivo quantification of brain compartment volume, and has many applications in cognitive, clinical and comparative neuroscience. There are numerous approaches for obtaining a brain volume estimate from MRI, and the primary focus of this paper is to ..."
Abstract - Cited by 5 (1 self) - Add to MetaCart
, the application of manual and automated MR image analysis techniques, and anatomical guidelines, providing the reader with enough information to decide on their approach at the outset of a quantitative MRI study. We advocate the use of stereology in conjunction with point counting for an unbiased and time

Automatic Brain Tissue Detection in Mri Images Using Seeded Region Growing

by Mehdi Jafari , Mehdi Jafari , Shohreh Kasaei - Segmentation and Neural Network Classification, Australian Journal of Basic and Applied Sciences, 5(8): 1066-1079, 2011, ISSN
"... Abstract: This paper presents a neural network-based method for automatic classification of magnetic resonance images (MRI) of brain under three categories of normal, lesion benign, and malignant. The proposed technique consists of six subsequent stages; namely, preprocessing, seeded region growing ..."
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Abstract: This paper presents a neural network-based method for automatic classification of magnetic resonance images (MRI) of brain under three categories of normal, lesion benign, and malignant. The proposed technique consists of six subsequent stages; namely, preprocessing, seeded region

ORIGINAL RESEARCH ADULT BRAIN MRI Texture Analysis Reveals Bulbar Abnormalities in

by Friedreich Ataxia
"... BACKGROUNDANDPURPOSE: Texture analysis is an image processing technique that can be used to extract parameters able to describe meaningful features of an image or ROI. Texture analysis based on the gray level co-occurrence matrix gives a second-order statistical description of the image or ROI. In t ..."
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BACKGROUNDANDPURPOSE: Texture analysis is an image processing technique that can be used to extract parameters able to describe meaningful features of an image or ROI. Texture analysis based on the gray level co-occurrence matrix gives a second-order statistical description of the image or ROI

Devi ―Segmentation of Tissues in Brain MRI Images using Dynamic Neuro-Fuzzy Technique

by S. Javeed Hussain, T. Satya Savithri, P. V. Sree Devi - International Journal of Soft Computing and Engineering (IJSCE , 2012
"... Abstract- In this paper, an efficient technique is proposed for the precise segmentation of normal and pathological tissues in the MRI brain images. The proposed segmentation technique initially performs classification process by utilizing Fuzzy Inference System (FIS) and FFBNN. Both classifiers are ..."
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technique is evaluated by performance measures such as accuracy, specificity and sensitivity. The performance of segmentation process is analyzed using a defined set of MRI brain image and compared against K-means clustering and Fuzzy ANN based segmentation methods.

A Robust Brain MRI Classification with GLCM Features

by Sahar Jafarpour, Zahra Sedghi, Mehdi Chehel Amirani
"... Automated and accurate classification of brain MRI is such important that leads us to present a new robust classification technique for analyzing magnetic response images. The proposed method consists of three stages, namely, feature extraction, dimensionality reduction, and classification. We use g ..."
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Automated and accurate classification of brain MRI is such important that leads us to present a new robust classification technique for analyzing magnetic response images. The proposed method consists of three stages, namely, feature extraction, dimensionality reduction, and classification. We use

Application of imaging techniques

by Michael A Reveley, Michael R Trimble
"... Studies of structural abnormalities in the functional psychoses using CT and MRI have confirmed the earlier findings of pneumoencephalography. Overall, the results indicate that about 20 % of schizophrenic and manic-depressive patients have ventricular enlargement and/or cortical atrophy. These abno ..."
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have suggested more abnormalities in the left, compared to the right hemisphere. The few MRI studies have found either no abnormality, or frontal lobe or corpus callosum abnormalities. The ability to assess regional brain function in vivo has already led to important advances in understanding

Active Mask Framework for Segmentation of Fluorescence Microscope Images

by Gowri Srinivasa, Advisor Prof, Prof Matthew, C. Fickus, Prof Adam, D. Linstedt, Prof Robert, F. Murphy
"... m]]l]]s¶D]]¿÷mB]iv]b]oD]m¶¨]iv]§]iv]r]j]t¿rv]]irj]]t]]m] / | ap]]r¿]ÎNy]s¶D]]mb¶r]ix} Û]Ix]]rd]mb]} p—N]t]o%ism] in]ty]m] / || Û]Is]¡uÎc]rN]]riv]nd]p]*N]m]st¶ I always bow to Śri ̄ Śāradāmbā, the limitless ocean of the nectar of compassion, who bears a rosary, a vessel of nectar, the symbol of ..."
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of knowledge and a book in Her lotus hands. Dedicated to the Lotus Feet of the revered Sadguru. This thesis presents a new active mask (AM) framework and an algorithm for segmenta-tion of digital images, particularly those of punctate patterns from fluorescence microscopy. Fluorescence microscopy has greatly

Proposing an Efficient Method to Classify MRI Images Based on Data Mining Techniques

by Mehdi Vatankhah
"... Nowadays, Magnetic Resonance Images (MRI) is the most common tool for diagnosis of soft tissues. Using fully automated classification magnetic resonance images of the human brain that are important for clinical research studies, can be detect the healthy or sick person. This paper purpose enhances t ..."
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Nowadays, Magnetic Resonance Images (MRI) is the most common tool for diagnosis of soft tissues. Using fully automated classification magnetic resonance images of the human brain that are important for clinical research studies, can be detect the healthy or sick person. This paper purpose enhances
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