OCTess: AN OPTICAL CHARACTER RECOGNITION ALGORITHM FOR AUTOMATED DATA EXTRACTION OF SPECTRAL DOMAIN OPTICAL COHERENCE TOMOGRAPHY REPORTS.

PURPOSE: Manual extraction of spectral domain optical coherence tomography (SD-OCT) reports is time and resource intensive. This study aimed to develop an optical character recognition (OCR) algorithm for automated data extraction from Cirrus SD-OCT macular cube reports. METHODS: SD-OCT monocular macular cube reports (n = 675) were randomly selected from a single-center database of patients from 2020 to 2023. Image processing and bounding box operations were performed, and Tesseract (an OCR library) was used to develop the algorithm, OCTess. The algorithm was validated using a separate test data set. RESULTS: The long short-term memory deep learning version of Tesseract achieved the best performance. After reverifying all discrepancies between human and algorithmic data extractions, OCTess achieved accuracies of 100.00% and 99.98% in the training (n = 125) and testing (n = 550) datasets, while the human error rate was 1.11% (98.89% accuracy) and 0.49% (99.51% accuracy) in each, respectively. OCTess extracted data in 3.1 seconds, compared with 94.3 seconds per report for human evaluators. CONCLUSION: We developed an OCR and machine learning algorithm that extracted SD-OCT data with near-perfect accuracy, outperforming humans in both accuracy and efficiency. This algorithm can be used for efficient construction of large-scale SD-OCT data sets for researchers and clinicians.

CASPER: An Integrated Software Platform for Rapid Development of CRISPR Tools.

Both academic and enterprise software solutions exist for designing CRISPR targets. They offer advantages when designing guide RNAs (gRNAs) but often focus on a select number of model organisms. Those that offer a wide variety of organisms can be limited in support of alternative endonucleases and downstream analyses such as multitargeting and population analyses to interrogate a microbiome. To accommodate broad CRISPR utilization, we developed a flexible platform software CRISPR Associated Software for Pathway Engineering and Research (CASPER) for gRNA generation and analysis in any organism and with any CRISPR-Cas system. CASPER combines traditional gRNA design tools with unique functions such as multiple Cas-type gRNA generation and evaluation of spacer redundancy in a single species or microbiome. The analyses have implications for strain-, species-, or genus-specific CRISPR diagnostic probe design and microbiome manipulation. The novel features of CASPER are packaged in a user-friendly interface to create a computational environment for researchers to streamline the utility of CRISPR-Cas systems.