지원사업
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
- 대한자기공명의과학회 Investigative Magnetic Resonance Imaging Investigative Magnetic Resonance Imaging 제24권 제4호
- 발행연도
- 2020.1
- 수록면
- 179 - 195 (17page)
이용수
초록· 키워드
오류제보하기
Recently, unsupervised deep learning methods have shown great potential in image processing. Compared with a large-amount demand for paired training data of supervised methods with a specific task, unsupervised methods can learn a universal and explicit prior information on data distribution and integrate it into the reconstruction process. Therefore, it can be used in various image reconstruction environments without showing degraded performance. The importance of unsupervised learning in MRI reconstruction appears to be growing. Nevertheless, the establishment of prior formulation in unsupervised deep learning varies a lot depending on mathematical approximation and network architectures. In this work, we summarized basic concepts of unsupervised deep learning comprehensively and compared performances of several state-of-the-art unsupervised learning methods for MRI reconstruction.
목차
등록된 정보가 없습니다.
참고문헌 (71)
참고문헌 신청
Heidemann RM / 2003 / A brief review of parallel magnetic resonance imaging / Eur Radiol 13:2323~2337
Donoho DL / 2006 / Compressed sensing / IEEE Trans Inf Theory 52:1289~1306
Liang D / 2009 / Accelerating SENSE using compressed sensing / Magn Reson Med 62:1574~1584
Huang J / 2011 / Efficient MR image reconstruction for compressed MR imaging / Med Image Anal 15:670~679
Lin FH / 2004 / Parallel imaging reconstruction using automatic regularization / Magn Reson Med 51:559~567
Donoho DL / 2006 / Compressed sensing / IEEE Trans Inf Theory 52:1289~1306
Liang D / 2009 / Accelerating SENSE using compressed sensing / Magn Reson Med 62:1574~1584
Huang J / 2011 / Efficient MR image reconstruction for compressed MR imaging / Med Image Anal 15:670~679
Lin FH / 2004 / Parallel imaging reconstruction using automatic regularization / Magn Reson Med 51:559~567
함께 읽어보면 좋을 논문
논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!
-
DEMO: Deep MR Parametric Mapping with Unsupervised Multi-Tasking Framework
Investigative Magnetic Resonance Imaging
2021 .12
-
Deep Learning in MR Image Processing
Investigative Magnetic Resonance Imaging
2019 .01
-
Unsupervised Deformable Image Registration Using Polyphase UNet for 3D Brain MRI Volumes
Investigative Magnetic Resonance Imaging
2020 .01
-
Deep Learning Applications in Perfusion MRI: Recent Advances and Current Challenges
Investigative Magnetic Resonance Imaging
2022 .12
-
Accelerating Magnetic Resonance Fingerprinting Using Hybrid Deep Learning and Iterative Reconstruction
Investigative Magnetic Resonance Imaging
2021 .12
-
Medical Image Analysis Using Artificial Intelligence
의학물리
2019 .01
-
Deep Learning in Dental Radiographic Imaging
대한소아치과학회지
2024 .02
-
IMF Reconstruction in Implant Breast Reconstruction
대한외과학회 학술대회 초록집
2017 .11
-
Fast Real-Time Cardiac MRI: a Review of Current Techniques and Future Directions
Investigative Magnetic Resonance Imaging
2021 .12
-
Unsupervised speckle noise reduction technique for clinical ultrasound imaging
ULTRASONOGRAPHY
2024 .09
-
Breast reconstruction statistics in Korea from the Big Data Hub of the Health Insurance Review and Assessment Service
Archives of plastic surgery : APS
2018 .01
-
Unsupervised clustering of multi-omics molecular layers reveals consensus molecular subtypes showing potential therapeutic opportunities for pancreatic cancer
Annals of Hepato-Biliary-Pancreatic Surgery
2021 .12
-
Current status of deep learning applications in abdominal ultrasonography
ULTRASONOGRAPHY
2021 .01
-
Deep-Learning-Based Molecular Imaging Biomarkers: Toward Data-Driven Theranostics
의학물리
2019 .01
-
New Methods of Implant Based Breast Reconstruction
대한임상종양학회 학술대회지
2018 .02
-
Deep Learning
Healthcare Informatics Research
2016 .01
-
Deep Learning in Nuclear Medicine and Molecular Imaging: Current Perspectives and Future Directions
Nuclear medicine and molecular imaging : NMMI
2018 .01
-
3D CT Reconstruction in Surgical Field
대한외과학회 학술대회 초록집
2022 .11
-
The Use of Anatomical Information for Molecular Image Reconstruction Algorithms: Attenuation/Scatter Correction, Motion Compensation, and Noise Reduction
Nuclear medicine and molecular imaging : NMMI
2016 .01
-
Impact of MRI and 3-D Ultrasound
대한외과학회 학술대회 초록집
2021 .11
이 논문의 저자 정보
최근 본 자료
댓글(0)
0