Experimental research on super-resolution reconstruction of medical MR image by deep learning network(PDF)
《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]
- Issue:
- 2021年第1期
- Page:
- 30-39
- Research Field:
- 医学影像物理
- Publishing date:
Info
- Title:
- Experimental research on super-resolution reconstruction of medical MR image by deep learning network
- Author(s):
- LIU Jiaqi; LIU Huanyu; LI Junbao
- Institute of Automation Test and Control, Harbin Institute of Technology, Harbin 150000, China
- Keywords:
- Keywords: MRI deep learning super-resolution
- PACS:
- R318；R445.2
- DOI:
- DOI:10.3969/j.issn.1005-202X.2021.01.006
- Abstract:
- Abstract: Based on an experimental research on super-resolution reconstruction of medical MR (Magnetic Resonance, MR) images by deep learning network, a large-scale high-quality data set for MR images super-resolution was proposed and constructed, which covers 4 parts: skull, knees, breasts, and head & neck. With the original images as the high-resolution, the original MRI images was down-sampled with the scale of ×2, ×3, ×4, and constituted MR image data at 3 different scales through data quality screening and different low-resolution image generation methods. The difficulty levels of super-resolution was anylyzed for different parts. 7 deep learning networks that achieved the best results in the super-resolution field of natural images were adopted and transfered to MR images to learn the mapping relationship from low-resolution MR images to high- and low-resolution MR images, and the super-resolution effects of these deep learning networks in natural images were comparatively analyzed. Through the experiment, it can be seen that the deep learning networks have achieved better results than traditional algorithms in MR image super-resolution, and some results are no less than those in natural images. The super-resolution effects of different parts are quite different, and it is difficult to give each parts an equally good effect by only using a deep learning network. Deep lExperimental research on super-resolution reconstruction of medical MR image by deep learning network earning networks will have important application value and theoretical significance in MR image super-resolution.
Last Update: 2021-01-29