Learning to segment cell nuclei in phase-contrast  microscopy from fluorescence images for drug discovery

Hana Mertanová; Jan Kybic; Jarmila Stanková; Petr Džubák; Marián Hajdúch

doi:10.1117/12.2607500

4 April 2022 Learning to segment cell nuclei in phase-contrast microscopy from fluorescence images for drug discovery

Hana Mertanová, Jan Kybic, Jarmila Stanková, Petr Džubák, Marián Hajdúch

Proceedings Volume 12032, Medical Imaging 2022: Image Processing; 120322L (2022) https://doi.org/10.1117/12.2607500
Event: SPIE Medical Imaging, 2022, San Diego, California, United States

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Abstract

We describe a method for analyzing geometrical properties of cell nuclei from phase contrast microscopy images. This is useful in drug discovery for quantifying the effect of candidate chemical compounds, bypassing the need for fluorescence imaging. Fluorescence images are then only used for training our nuclei segmentation, avoiding the need for the time consuming expert annotations. Geometry based descriptors are calculated and aggregated and fed into a classifier to distinguish the different types of chemical treatments. The drug treatment can be distinguished from no treatment with accuracy better than 95% from fluorescence images and better than 77% from phase contrast images.

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Hana Mertanová, Jan Kybic, Jarmila Stanková, Petr Džubák, and Marián Hajdúch "Learning to segment cell nuclei in phase-contrast microscopy from fluorescence images for drug discovery", Proc. SPIE 12032, Medical Imaging 2022: Image Processing, 120322L (4 April 2022); https://doi.org/10.1117/12.2607500

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