3D multiplexed tissue imaging reconstruction and optimized region of interest (ROI) selection through deep learning model of channels embedding.

Burlingame, Erik; Ternes, Luke; Lin, Jia-Ren; Chen, Yu-An; Kim, Eun Na; Gray, Joe W; Chang, Young Hwan

Burlingame, Erik; Ternes, Luke; Lin, Jia-Ren; Chen, Yu-An; Kim, Eun Na; Gray, Joe W; Chang, Young Hwan.

Afiliação

Burlingame E; Department of Biomedical Engineering and Computational Biology Program, Oregon Health and Science University, Portland, OR, United States.
Ternes L; Department of Biomedical Engineering and Computational Biology Program, Oregon Health and Science University, Portland, OR, United States.
Lin JR; Ludwig Center for Cancer Research at Harvard, Harvard Medical School, Boston, MA, United States.
Chen YA; Laboratory of Systems Pharmacology, Harvard Medical School, Boston, MA, United States.
Kim EN; Ludwig Center for Cancer Research at Harvard, Harvard Medical School, Boston, MA, United States.
Gray JW; Laboratory of Systems Pharmacology, Harvard Medical School, Boston, MA, United States.
Chang YH; Department of Biomedical Engineering and Computational Biology Program, Oregon Health and Science University, Portland, OR, United States.

Front Bioinform ; 3: 1275402, 2023.

Article em En | MEDLINE | ID: mdl-37928169

Palavras-chave

3D multiplex tissue imaging; 3D virtual CyCIF; channels embedding; multimodal integration; optimized region of interest selection

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Bioinform Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos

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