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作者机构:1School of Computer Science & Technology Nanjing Normal University Nanjing 210023 China 2Department of Electrical Engineering Federal University of Santa Catarina Florianópolis Brazil
出 版 物:《AIP Conference Proceedings》
年 卷 期:2018年第1955卷第1期
摘 要:In order to develop a novel alcoholism detection method, we proposed a magnetic resonance imaging (MRI)-based computer vision approach. We first use contrast equalization to increase the contrast of brain slices. Then, we perform Haar wavelet transform and principal component analysis. Finally, we use back propagation neural network (BPNN) as the classification tool. Our method yields a sensitivity of 81.71±4.51%, a specificity of 81.43±4.52%, and an accuracy of 81.57±2.18%. The Haar wavelet gives better performance than db4 wavelet and sym3 wavelet.