Harnessing Coded Ptychography to Deliver AI-powered Evaluation of Unstained Lung Biopsies at the Point-Of-Care

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The parent Phase I SBIR grant aims to analyze quantitative phase imaging of lung FNAs using coded ptychography microscopy captured at different wavelengths of light (Specific Aim #1), and demonstrate that Al can correctly detect cells on unstained phase images (Specific Aim #2). Engaging the supplementee, Arianna Pryor, to directly support specific aim #2 is expected to allow us to pursue a more diverse solution space for Al model development to detect cells on the unstained QPI imaging, resulting in a more robust solution and amplifying the results and impact of the parent grant. Ms. Pryer's experience in Al model development for lung cytology, in conjunction with her education in biomedical engineering makes her an ideal candidate for the project. Additionally, the technical experience and mentoring, direct clinician interactions and entrepreneurial experience gained through working in a startup directly supports her growth and future career goals.