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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국지능시스템학회 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS Vol.19 No.4
- 발행연도
- 2019.12
- 수록면
- 315 - 322 (8page)
- DOI
- 10.5391/IJFIS.2019.19.4.315
이용수
초록· 키워드
오류제보하기
Artificial intelligence enhances the boundaries and capabilities of medical imaging. Hence, researchers are continuously attempting to develop an efficient and automated diagnosis system to increase the accuracy and performance to diagnose the brain abnormality. Therefore, it is required that a suitable method to diagnose and classify brain-related diseases such as Alzheimer disease, cancer, dementia, etc. Magnetic resonance imaging (MRI) is a powerful imaging technique in neuroscience for studying brain images. In the past years, many brain MRI classification techniques were proposed. Machine learning and deep learning have demonstrated a wonderful performance in the classification task. In this paper, the study of various brain MRI classification techniques has been provided. The aim of this study is to help the doctors/neurologists in selection of appropriate classification method based on several parameters like accuracy, computer complexity, and low training data availability. We also analyze and compare the performance of different classification methods based on several evaluation metrics.
목차
Abstract
1. Introduction
2. Classification Approaches for Human Brain MRI Images
3. Performance Analysis of Classification Methods
4. Concluding Remarks
References
참고문헌 (18)
참고문헌 신청
I. Despotovic / 2015 / MRI segmentation of the human brain: challenges, methods, and applications / Computational and Mathematical Methods in Medicine 2015:450341
Nishant Chauhan / 2018 / Performance Analysis of Denoising Algorithms for Human Brain Image / International Journal of Fuzzy Logic and Intelligent systems 18(3):175~181
Nishant Chauhan / 2019 / Denoising Approaches Using Fuzzy Logic and Convolutional Autoencoders for Human Brain MRI Image / International Journal of Fuzzy Logic and Intelligent systems 19(3):135~139
A. Bargaje / 2017 / Review of classification algorithms for brain MRI images / International Research Journal of Engineering and Technology 4(1):678~682
Gopal S. Tandel / 2019 / A Review on a Deep Learning Perspective in Brain Cancer Classification / Cancers 11(1):111
Nishant Chauhan / 2018 / Performance Analysis of Denoising Algorithms for Human Brain Image / International Journal of Fuzzy Logic and Intelligent systems 18(3):175~181
Nishant Chauhan / 2019 / Denoising Approaches Using Fuzzy Logic and Convolutional Autoencoders for Human Brain MRI Image / International Journal of Fuzzy Logic and Intelligent systems 19(3):135~139
A. Bargaje / 2017 / Review of classification algorithms for brain MRI images / International Research Journal of Engineering and Technology 4(1):678~682
Gopal S. Tandel / 2019 / A Review on a Deep Learning Perspective in Brain Cancer Classification / Cancers 11(1):111
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