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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 중앙대학교 영상콘텐츠융합연구소MINT Moving Image & Technology (MINT) MINT: Moving Image & Technology, Vol.3, No.2
- 발행연도
- 2023.8
- 수록면
- 6 - 14 (9page)
- DOI
- 10.15323/mint.2023.8.3.2.6
이용수
초록· 키워드
오류제보하기
Recent developments in the field of deep learning have brought about numerous changes in the world. Deep learning has had a significant impact on a wide range of fields, including medical care, gaming, autonomous driving, and aerospace, producing remarkable results. In particular, deep learning is demonstrating excellent performance in the field of computer vision. The field of healthcare is closely connected to computer vision, and applying deep learning to medical images is an important and challenging task. Deep learning has played a crucial role in advancing medical image analysis. Researchers have explored the application of deep learning techniques to medical images, and have published many remarkable results. Medical image analysis can be broadly categorized into several areas, such as classification, segmentation, augmentation, and registration. This paper aims to provide a brief overview of important models of deep neural networks (DNNs), which are the foundation of deep learning, and discuss their applications in medical image segmentation tasks.
목차
Abstract
1. Introduction
2. Deep Neural Networks (DNNs)
3. DNNs for Medical Image Segmentation
4. Conclusion
References
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