Fully Automated OCT-based Tissue Screening System

TL;DR

This paper presents an automated OCT imaging system with deep learning segmentation for high-throughput ex vivo tissue screening, demonstrating rapid, reliable, and unbiased tissue analysis for drug discovery and research.

Contribution

The study introduces a fully automated OCT-based tissue screening system with custom hardware and transformer-based segmentation, enhancing throughput and accuracy in tissue analysis.

Findings

Validated on retinal explant cultures from a mouse model.

Provides rapid, reliable, and unbiased tissue readouts.

Transforms drug discovery and tissue screening processes.

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.