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Cellpose+, a Morphological Analysis Tool for Feature Extraction of Stained Cell Images by Huaman, Israel A.; Ghorabe, Fares D. E.; Chumakova, Sofya S.; Pisarenko, Alexandra A.; Dudaev, Alexey E.; Volova, Tatiana G.; Ryltseva, Galina A.; Ulasevich, Sviatlana A.; Shishatskaya, Ekaterina I.; Skorb, Ekaterina V.; Zun, Pavel S. is a scholarly article available to read on EtoBox.

What is Cellpose+, a Morphological Analysis Tool for Feature Extraction of Stained Cell Images about?

Advanced image segmentation and processing tools present an opportunity to study cell processes and their dynamics. However, image analysis is often routine and time-consuming. Nowadays, alternative data-driven approaches using deep learning are potentially offering automatized, accurate, and fast image analysis. In this paper, we extend the applications of Cellpose, a state-of-the-art cell segmentation framework, with feature extraction capabilities to assess morphological characteristics. We also introduce a dataset of DAPI and FITC stained cells to which our new method is applied.

Author

Huaman, Israel A.; Ghorabe, Fares D. E.; Chumakova, Sofya S.; Pisarenko, Alexandra A.; Dudaev, Alexey E.; Volova, Tatiana G.; Ryltseva, Galina A.; Ulasevich, Sviatlana A.; Shishatskaya, Ekaterina I.; Skorb, Ekaterina V.; Zun, Pavel S.

Published

2024

Language

EN