Work

Cellpose+, a Morphological Analysis Tool for Feature Extraction of Stained Cell Images

Year: 2025

Type: article

Abstract: 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 4′,6‐diamidino‐2‐phenylindole and fluorescein isothiocyanate stained cells to which our new method is applied.

Source: Advanced Intelligent Discovery

DOI: 10.1002/aidi.202500005

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

Institutions: ITMO University, Russian Academy of Sciences, Institute of Biophysics, Siberian Federal University

Language: English

Topic: Cell Image Analysis Techniques

Subfield: Biophysics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: diamond

OpenAlex ID: W4411430693

FWCI: 1.45

Cites: 44

Cited by: 4

Related to: 10