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초록

영어

This study examines the innovative applications and future prospects of Convolutional Neural Networks (CNN) in the field of medical image analysis. CNNs significantly enhance the accuracy and efficiency of medical image diagnostics through their powerful data processing and feature extraction capabilities. This review analyzes various CNN architectures and recent technological advancements, highlighting the importance of transfer learning and data augmentation techniques. It also discusses the potential for integrated multi-modality data analysis and real-time clinical applications, while emphasizing the need for ethical considerations and data security. This research underscores the potential of CNN technology to improve healthcare quality and contribute to patient health management.

목차

Abstract
1. 서론
2. 기술적 배경
3. 문헌 리뷰
4. 적용 분야
4.1 질병 진단 및 예측
4.2. 영상 분할 및 병변 탐지
4.3. 정량적 분석과 치료 효과의 평가
4.4. 의료 영상 통합 및 복합 분석
5. 모 델링 의 개발 절차
6. 논의
References

키워드

합성곱 신경망 의료 이미지 분석 전이 학습 데이터 증강 다중 모달리티 데이터 분석 데이터 보안 Convolutional Neural Networks Medical Image Analysis Transfer Learning Data Augmentation Multi-modality Data Analysis Data Security

저자

• 변해원 [ Haewon Byeon | Dept. of Future Technology, Korea University of Technology and Education, South Korea ] Corresponding Author

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