Publisher
Springer Science and Business Media LLC
Subject
Health Informatics,Radiology, Nuclear Medicine and imaging,General Medicine,Surgery,Computer Graphics and Computer-Aided Design,Computer Science Applications,Computer Vision and Pattern Recognition,Biomedical Engineering
Reference23 articles.
1. Wei S, Zhou X, Wu W, Pu Q, Wang Q, Yang X (2018) Medical image super-resolution by using multi-dictionary and random forest. Sustain Cities Soc. https://doi.org/10.1016/j.scs.2017.11.012
2. Li Y, Song B, Guo J, Du X, Guizani M (2019) Super-resolution of brain MRI images using overcomplete dictionaries and nonlocal similarity. IEEE Access 7:25897–25907
3. Zhang F, Wu Y, Xiao Z, Geng L, Wu J, Wen J, Wang W, Liu P (2019) Super resolution reconstruction for medical image based on adaptive multi-dictionary learning and structural self-similarity. Comput Assist Surg 24:81–88
4. Li H, Lam K-M, Li D (2018) Joint maximum purity forest with application to image super-resolution. J Electron Imaging 27:43005
5. Grabner A, Poier G, Opitz M, Schulter S, Roth PM (2017) Loss-specific training of random forests for super-resolution. Comput Complex 35:39
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献