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Fully Automated OCT-based Tissue Screening System.
Pi, Shaohua; Ganjee, Razieh; Wang, Lingyun; Arbuckle, Riley K; Zhao, Chengcheng; Sahel, Jose A; Wang, Bingjie; Chen, Yuanyuan.
Afiliação
  • Pi S; Department of Ophthalmology, University of Pittsburgh, Pittsburgh, PA 15213, USA.
  • Ganjee R; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA.
  • Wang L; Department of Ophthalmology, University of Pittsburgh, Pittsburgh, PA 15213, USA.
  • Arbuckle RK; Department of Ophthalmology, University of Pittsburgh, Pittsburgh, PA 15213, USA.
  • Zhao C; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA.
  • Sahel JA; Department of Ophthalmology, University of Pittsburgh, Pittsburgh, PA 15213, USA.
  • Wang B; Department of Pharmacology and Chemical Biology, University of Pittsburgh, Pittsburgh, PA 15213, USA.
  • Chen Y; Department of Human Genetics, University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA 15213, USA.
ArXiv ; 2024 May 15.
Article em En | MEDLINE | ID: mdl-38800655
ABSTRACT
This study introduces a groundbreaking optical coherence tomography (OCT) imaging system dedicated for high-throughput screening applications using ex vivo tissue culture. Leveraging OCT's non-invasive, high-resolution capabilities, the system is equipped with a custom-designed motorized platform and tissue detection ability for automated, successive imaging across samples. Transformer-based deep learning segmentation algorithms further ensure robust, consistent, and efficient readouts meeting the standards for screening assays. Validated using retinal explant cultures from a mouse model of retinal degeneration, the system provides robust, rapid, reliable, unbiased, and comprehensive readouts of tissue response to treatments. This fully automated OCT-based system marks a significant advancement in tissue screening, promising to transform drug discovery, as well as other relevant research fields.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: ArXiv Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: ArXiv Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos
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