Тип публикации: статья из журнала

Год издания: 2025

Идентификатор DOI: 10.1002/aidi.202500005

Аннотация: <jats:p>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 paПоказать полностьюper, we extend the applications of <jats:italic>Cellpose</jats:italic>, a state-of-the-art cell segmentation framework, with feature extraction capabilities to assess morphological characteristics. We also introduce a dataset of 4′,6-diamidino-2-phenylindole and fluorescein isothiocyanate stained cells to which our new method is applied.</jats:p>

Журнал: Advanced Intelligent Discovery

Номера страниц: 202500005

ISSN журнала: 29439981

Издатель: Wiley

• Huaman Israel A. (Infochemistry Scientific Center ITMO University St. Petersburg Russia)
• Ghorabe Fares D. E. (Infochemistry Scientific Center ITMO University St. Petersburg Russia)
• Chumakova Sofya S. (Infochemistry Scientific Center ITMO University St. Petersburg Russia)
• Pisarenko Alexandra A. (Infochemistry Scientific Center ITMO University St. Petersburg Russia)
• Dudaev Alexey E. (Siberian Division Institute of Biophysics Russian Academy of Science Krasnoyarsk Russia)
• Volova Tatiana G. (School of Fundamental Biology and Biotechnology Siberian Federal University Krasnoyarsk Russia)
• Ryltseva Galina A. (Siberian Division Institute of Biophysics Russian Academy of Science Krasnoyarsk Russia)
• Ulasevich Sviatlana A. (Infochemistry Scientific Center ITMO University St. Petersburg Russia)
• Shishatskaya Ekaterina I. (Infochemistry Scientific Center ITMO University St. Petersburg Russia)
• Skorb Ekaterina V. (Infochemistry Scientific Center ITMO University St. Petersburg Russia)
• Zun Pavel S. (Infochemistry Scientific Center ITMO University St. Petersburg Russia)

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