Adaptive Neuro-Fuzzy Inference System for brain abnormality segmentation

N. M. Noor, N. Khalid, R. Hassan, Shafaf Ibrahim, I. Yassin
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引用次数: 19

Abstract

This paper studies the application of the Adaptive Neuro-Fuzzy Inference System (ANFIS) for segmentation of brain abnormality in MRI images. Segmentation of MRI image is an important part of brain imaging research. In this study, 150 MRI images were used as testing data for the system. The data was created by combining the shapes and size of various abnormalities and pasting it onto normal brain image. Several types of backgrounds were tested — low, medium and high grey levels. The experimental results show good segmentation for medium and low background levels value for both light and dark abnormality levels over different backgrounds.
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脑异常分割的自适应神经模糊推理系统
研究了自适应神经模糊推理系统(ANFIS)在MRI脑异常图像分割中的应用。MRI图像分割是脑成像研究的重要组成部分。本研究使用150张MRI图像作为该系统的测试数据。这些数据是通过结合各种异常的形状和大小,并将其粘贴到正常的大脑图像上而创建的。测试了几种类型的背景——低、中、高灰度。实验结果表明,该方法对不同背景下的明暗异常值都能很好地分割出中低背景值。
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