1. Defining the boundaries: challenges and advances in identifying cells in microscopy images.
- Author
-
Gogoberidze N and Cimini BA
- Subjects
- Image Processing, Computer-Assisted methods, Microscopy methods, Algorithms
- Abstract
Segmentation, or the outlining of objects within images, is a critical step in the measurement and analysis of cells within microscopy images. While improvements continue to be made in tools that rely on classical methods for segmentation, deep learning-based tools increasingly dominate advances in the technology. Specialist models such as Cellpose continue to improve in accuracy and user-friendliness, and segmentation challenges such as the Multi-Modality Cell Segmentation Challenge continue to push innovation in accuracy across widely varying test data as well as efficiency and usability. Increased attention on documentation, sharing, and evaluation standards is leading to increased user-friendliness and acceleration toward the goal of a truly universal method., Competing Interests: Declaration of Competing Interest The authors declare that there are no competing interests associated with the paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)
- Published
- 2024
- Full Text
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