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영문 논문지

홈 홈 > 연구문헌 > 영문 논문지 > IEIE Transactions on Smart Processing & Computing (IEIE SPC)

IEIE Transactions on Smart Processing & Computing (IEIE SPC)

Current Result Document : 1,143 / 1,143

한글제목(Korean Title) Development of an Efficient Cascade Pathological-Brain Detection System using a Median Filter and Quadratic Discriminant Analysis
영문제목(English Title) Development of an Efficient Cascade Pathological-Brain Detection System using a Median Filter and Quadratic Discriminant Analysis
저자(Author) Debesh Jha   Goo-Rak Kwon                             
원문수록처(Citation) VOL 07 NO. 02 PP. 0140 ~ 0147 (2018. 04)
한글내용
(Korean Abstract)
영문내용
(English Abstract)
This research article proposes smart utilization of a machine learning technique to discriminate between normal and pathological brain images. The method is based on the following computational technique: a median filter is utilized for pre-processing input images; discrete wavelet transform (DWT) is utilized for feature extraction; principal component analysis (PCA) minimizes the dimensionality of the wavelet coefficients; and quadratic discriminate analysis (QDA) classifies the reduced features as normal or pathological. Experiments were carried out on 90 images (five normal and 85 pathological) from a Harvard Medical School dataset. The proposed system yielded excellent classification accuracy of 98.90% with 10× 5-fold stratified cross-validation (SCV). Moreover, the proposed technique outperforms seven state-of-the-art algorithms in terms of accuracy. Furthermore, our method signifies its effectiveness when compared with other machine learning approaches.
키워드(Keyword) Wavelet transform   Principal component analysis   Stratified cross-validation   Quadratic discriminant analysis                       
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