Extracting morphologies from third harmonic generation images of structurally normal human brain tissue | Zendy

Andy Zhang | Zendy; Nikolay V. Kuzmin | Zendy; Marie Louise Groot | Zendy; Jan C. de Munck | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Extracting morphologies from third harmonic generation images of structurally normal human brain tissue

Author(s) -

Andy Zhang,

Nikolay V. Kuzmin,

Marie Louise Groot,

Jan C. de Munck

Publication year - 2017

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/btx035

Subject(s) - computer science , correctness , segmentation , artificial intelligence , pattern recognition (psychology) , neuropil , benchmark (surveying) , computer vision , image (mathematics) , image segmentation , human brain , software , algorithm , biology , neuroscience , programming language , geography , central nervous system , geodesy

The morphologies contained in 3D third harmonic generation (THG) images of human brain tissue can report on the pathological state of the tissue. However, the complexity of THG brain images makes the usage of modern image processing tools, especially those of image filtering, segmentation and validation, to extract this information challenging.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research