利用磁共振光谱信号对代谢性脑疾病进行模糊分类

NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2008-05-19 DOI:10.1109/NAFIPS.2008.4531247

S. Z. Mahmoodabadi, J. Alirezaie, P. Babyn

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引用次数: 2

摘要

疑似代谢性脑紊乱对医生和病人来说都是一个困难的挑战。我们已经开发了一个全自动系统，以分类磁共振光谱(MRS)信号。本研究设计了新的模糊规则和模糊分类器对儿童代谢性脑疾病进行分类。在检测5种代谢性脑疾病时，达到了75%的灵敏度和阳性预测值。

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Fuzzy classification of metabolic brain diseases utilizing MR Spectroscopy signals

A suspected metabolic brain disorder presents a difficult challenge to the physician and the patient. We have developed a fully automated system in order to classify the Magnetic Resonance Spectroscopy (MRS) signals. Novel fuzzy rules and a fuzzy classifier have been designed in this study to categorize metabolic brain diseases in children. The sensitivity and positive predictivity of 75% plusmn 43 in detecting five metabolic brain diseases have been achieved.

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NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society

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