Segmentation of magnetic resonance images using fuzzy algorithms for learning vector quantization

1999 ◽  
Vol 18 (2) ◽  
pp. 172-180 ◽  
Author(s):  
N.B. Karayiannis ◽  
Pin-I Pai
Keyword(s):  
Magnetic Resonance ◽  
Vector Quantization ◽  
Learning Vector Quantization ◽  
Magnetic Resonance Images ◽  
Fuzzy Algorithms

scholarly journals Round Randomized Learning Vector Quantization for Brain Tumor Imaging

2016 ◽  
Vol 2016 ◽  
pp. 1-19 ◽  
Author(s):  
Siti Norul Huda Sheikh Abdullah ◽  
Farah Aqilah Bohani ◽  
Baher H. Nayef ◽  
Shahnorbanun Sahran ◽  
Omar Al Akash ◽  
...  
Keyword(s):  
Brain Tumor ◽  
Magnetic Resonance ◽  
Vector Quantization ◽  
Distance Function ◽  
Euclidean Distance ◽  
Brain Magnetic Resonance Imaging ◽  
Learning Vector Quantization ◽  
Magnetic Resonance Images ◽  
Class Distribution ◽  
Euclidean Distance Function

Brain magnetic resonance imaging (MRI) classification into normal and abnormal is a critical and challenging task. Owing to that, several medical imaging classification techniques have been devised in which Learning Vector Quantization (LVQ) is amongst the potential. The main goal of this paper is to enhance the performance of LVQ technique in order to gain higher accuracy detection for brain tumor in MRIs. The classical way of selecting the winner code vector in LVQ is to measure the distance between the input vector and the codebook vectors using Euclidean distance function. In order to improve the winner selection technique, round off function is employed along with the Euclidean distance function. Moreover, in competitive learning classifiers, the fitting model is highly dependent on the class distribution. Therefore this paper proposed a multiresampling technique for which better class distribution can be achieved. This multiresampling is executed by using random selection via preclassification. The test data sample used are the brain tumor magnetic resonance images collected from Universiti Kebangsaan Malaysia Medical Center and UCI benchmark data sets. Comparative studies showed that the proposed methods with promising results are LVQ1, Multipass LVQ, Hierarchical LVQ, Multilayer Perceptron, and Radial Basis Function.

An emerging technology: Nuclear magnetic resonance microscopy

1988 ◽  
Vol 46 ◽  
pp. 1000-1001
Author(s):  
M.J. Hennessy ◽  
E. Kwok
Keyword(s):  
Nuclear Magnetic Resonance ◽  
Magnetic Resonance ◽  
Relaxation Times ◽  
Basic Research ◽  
Local Environment ◽  
Magnetic Resonance Images ◽  
Nmr Microscopy ◽  
Mri Scans ◽  
Temperature Relaxation ◽  
Nuclear Magnetic

Much progress in nuclear magnetic resonance microscope has been made in the last few years as a result of improved instrumentation and techniques being made available through basic research in magnetic resonance imaging (MRI) technologies for medicine. Nuclear magnetic resonance (NMR) was first observed in the hydrogen nucleus in water by Bloch, Purcell and Pound over 40 years ago. Today, in medicine, virtually all commercial MRI scans are made of water bound in tissue. This is also true for NMR microscopy, which has focussed mainly on biological applications. The reason water is the favored molecule for NMR is because water is,the most abundant molecule in biology. It is also the most NMR sensitive having the largest nuclear magnetic moment and having reasonable room temperature relaxation times (from 10 ms to 3 sec). The contrast seen in magnetic resonance images is due mostly to distribution of water relaxation times in sample which are extremely sensitive to the local environment.

Functional information from magnetic resonance imaging

1995 ◽  
Vol 53 ◽  
pp. 84-85
Author(s):  
Alan P. Koretsky ◽  
Afonso Costa e Silva ◽  
Yi-Jen Lin
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
High Resolution ◽  
Cancer Biology ◽  
Imaging Modality ◽  
Magnetic Resonance Images ◽  
Great Success ◽  
Functional Information ◽  
Resonance Imaging ◽  
High Resolution Mri

Magnetic resonance imaging (MRI) has become established as an important imaging modality for the clinical management of disease. This is primarily due to the great tissue contrast inherent in magnetic resonance images of normal and diseased organs. Due to the wide availability of high field magnets and the ability to generate large and rapidly switched magnetic field gradients there is growing interest in applying high resolution MRI to obtain microscopic information. This symposium on MRI microscopy highlights new developments that are leading to increased resolution. The application of high resolution MRI to significant problems in developmental biology and cancer biology will illustrate the potential of these techniques.In combination with a growing interest in obtaining high resolution MRI there is also a growing interest in obtaining functional information from MRI. The great success of MRI in clinical applications is due to the inherent contrast obtained from different tissues leading to anatomical information.

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