A convolutional neural network for common coordinate registration of high-resolution histology images | Zendy

Aidan C. Daly | Zendy; Krzysztof J. Geras | Zendy; Richard Bonneau | Zendy

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A convolutional neural network for common coordinate registration of high-resolution histology images

Author(s) -

Aidan C. Daly,

Krzysztof J. Geras,

Richard Bonneau

Publication year - 2021

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btab447

Subject(s) - computer science , convolutional neural network , artificial intelligence , segmentation , deep learning , pattern recognition (psychology) , image registration , process (computing) , image resolution , transfer of learning , source code , computer vision , image (mathematics) , operating system

Registration of histology images from multiple sources is a pressing problem in large-scale studies of spatial -omics data. Researchers often perform 'common coordinate registration', akin to segmentation, in which samples are partitioned based on tissue type to allow for quantitative comparison of similar regions across samples. Accuracy in such registration requires both high image resolution and global awareness, which mark a difficult balancing act for contemporary deep learning architectures.

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