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Change detection based on unsupervised sparse representation for fundus image pair

Detecting changes is an important issue for ophthalmology to compare longitudinal fundus images at different stages and obtain change regions. Illumination variations bring distractions on the change regions by the pixel-by-pixel comparison. In this paper, a new unsupervised change detection method...

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Detalles Bibliográficos
Autores principales:	Fu, Yinghua, Zhao, Xing, Liang, Yong, Zhao, Tiejun, Wang, Chaoli, Zhang, Dawei
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Nature Publishing Group UK 2022
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9197950/ https://www.ncbi.nlm.nih.gov/pubmed/35701500 http://dx.doi.org/10.1038/s41598-022-13754-5

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