Fully Automated OCT-based Tissue Screening System

Shaohua Pi, Razieh Ganjee, Lingyun Wang, Riley K. Arbuckle, Chengcheng Zhao +3 more
5/15/2024
physics.med-phcs.CV

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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.

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Cite this paper

@article{pi2024fully,
  title  = {Fully Automated OCT-based Tissue Screening System},
  author = {Shaohua Pi and Razieh Ganjee and Lingyun Wang and Riley K. Arbuckle and Chengcheng Zhao and Jose A Sahel and Bingjie Wang and Yuanyuan Chen},
  year   = {2024},
  eprint = {2405.09601},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2405.09601v1}
}

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