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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 대한전자공학회 IEIE Transactions on Smart Processing & Computing IEIE Transactions on Smart Processing & Computing Vol.7 No.2
- 발행연도
- 2018.4
- 수록면
- 140 - 147 (8page)
- DOI
- 10.5573/IEIESPC.2018.7.2.140
이용수
초록· 키워드
오류제보하기
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 crossvalidation (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.
목차
Abstract
1. Introduction
2. Methodology
3. Results and Discussions
4. Comparison to Existing State-of-the-art Methods
5. Conclusion
References
참고문헌 (24)
참고문헌 신청
[학술지(정기간행물)] - S. Chaplot / 2006 / Classification of magnetic resonance brain images using wavelets as input to support vector machine and neural network / Biomedical Signal Processing and Control 1 (1) : 86 ~ 92
[학술지(정기간행물)] - L. M. Fletcher-Heath / 2001 / Automatic segmentation of non-enhancing brain tumours in magnetic resonance images / Artif. Intell. Med 21 : 43 ~ 63
[학술지(정기간행물)] - H. Fujita / 2008 / Computer-aided diagnosis: The emerging of three CAD systems / Japanese health care need Computer Methods and Programs in Biomedicine 92 (3) : 238 ~ 248
[학술지(정기간행물)] - P. Maji / 2008 / Second order fuzzy measure and weighted co‐occurrence matrix for segmentation of brain MR images / Fund Inform 88 : 161 ~ 176
[학술지(정기간행물)] - H. Arimura / 2009 / Computer-aided diagnosis systems for brain diseases in magnetic resonance images / algorithms 2 (3) : 925 ~ 952
[학술지(정기간행물)] - L. M. Fletcher-Heath / 2001 / Automatic segmentation of non-enhancing brain tumours in magnetic resonance images / Artif. Intell. Med 21 : 43 ~ 63
[학술지(정기간행물)] - H. Fujita / 2008 / Computer-aided diagnosis: The emerging of three CAD systems / Japanese health care need Computer Methods and Programs in Biomedicine 92 (3) : 238 ~ 248
[학술지(정기간행물)] - P. Maji / 2008 / Second order fuzzy measure and weighted co‐occurrence matrix for segmentation of brain MR images / Fund Inform 88 : 161 ~ 176
[학술지(정기간행물)] - H. Arimura / 2009 / Computer-aided diagnosis systems for brain diseases in magnetic resonance images / algorithms 2 (3) : 925 ~ 952
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UCI(KEPA) : I410-ECN-0101-2018-569-002044356