Holographic microscopy- and artificial intelligence-based digital pathology for the next generation of cytology in veterinary medicine (VetCyto)

Project title: Holographic microscopy- and artificial intelligence-based digital pathology for the next generation of cytology in veterinary medicine (VetCyto)
Project number: lzp-2023/1-0220
Project applicant: University of Latvia (UL)
Project cooperation partner: Institute of Electronics and Computer Science (IECS)
Research manager:  PhD Blaz Cugmas
Project implementation deadline: 01.01.2024. – 31.12.2026.
Total funding of the project: 299 994,00 EUR including the funding allocated to the UL part of the project 214 457, 00 EUR and the part of the IECS 85 537,00 EUR
Planned project results:
•    original scientific articles the quoting index whereof reaches at least 50 per cent of the average quoting index of the sector which have been submitted or accepted for publication in the journals or conference symposia included in Web of Science Core Collection or SCOPUS databases – 3
•    original scientific articles submitted or accepted for publication in the journals or conference symposia included in Web of Science Core Collection or SCOPUS databases – 6
•    scientific databases and data sets developed within the scope of the project – 2 
•   functional models – 2  
•    new non-commercial treatment and diagnostic methods – 1 
•    project proposal submitted in an international or national call for research and development projects – 1 
•    successfully defended master’s thesis within the thematic focus of the project – 1 
•    doctoral thesis successfully defended according to certain procedures within the thematic focus of the project – 1 
Project Summary:
Cytology is a necessary diagnostic test performed daily by veterinary clinicians. Microscopic examination of individual cells or cell clusters on stained or native slides can reveal various diseases like tumors and parasites. Particular knowledge, experience, and significant time are needed to interpret the sample on-site. Alternatively, certified pathologists can review the slides directly or via whole slide imaging (WSI)-based digital pathology systems, leading to diagnostic delays and extra costs. We propose high-resolution wide-field optical imaging for cytology in veterinary clinics. The project aims to validate holographic microscopy (HM) for automated cytological examination of common conditions in dogs, cats, and cows: inflammation, tumors, and parasites. HM systems are portable and offer computationally cost-effective image reconstruction, including artificial intelligence (AI), which enables direct training from raw holographic images. Because HM is lensless microscopy, its field of view (FoV) is unrelated to the image resolution and matches the camera’s sensor size (tens of mm2 ) at ×1 magnification. The proposed pixel superresolution strategy (PSRS) will investigate the variety of HM adjustable factors, including the illumination angle, wavelength, and modification in the sample-to-sensor distance, to obtain submicron pixel resolution at wide FoV. Digital focusing also guarantee a broader depth of field, crucial for focused images throughout cytological slides regardless of the thickness of the sample. Finally, the state-of-the-art AI algorithms will extract essential cytological features from the acquired images and reach a primary diagnosis. The proposed project is an essential step towards a clinically applicable, automated, fast, and costeffective digital pathology system for veterinary cytology, which can improve animal health and increase the competitiveness of veterinary science and business.