ArticleBiomedical optics express2023
Volumetric segmentation of biological cells and subcellular structures for optical diffraction tomography images.
Article in Biomedical optics express, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed, 4 citations in OpenAlex.
- Lightweight and precise cell classification based on holographic tomography-derived refractive index point cloud.Journal of biomedical optics · 2025Article
- Volumetric segmentation of biological cells and subcellular structures for optical diffraction tomography images.Biomedical optics express · 2023Article
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Authors and funding
2 authors at 1 institution in 1 country.
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Abstract
Three-dimensional, quantitative imaging of biological cells and their internal structures performed by optical diffraction tomography (ODT) is an important part of biomedical research. However, conducting quantitative analysis of ODT images requires performing 3D segmentation with high accuracy, often unattainable with available segmentation methods. Therefore, in this work, we present a new semi-automatic method, called ODT-SAS, which combines several non-machine-learning techniques to segment cells and 2 types of their organelles: nucleoli and lipid structures (LS). ODT-SAS has been compared with Cellpose and slice-by-slice manual segmentation, respectively, in cell segmentation and organelles segmentation. The comparison shows superiority of ODT-SAS over Cellpose and reveals the potential of our technique in detecting cells, nucleoli and LS.
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Registered trials
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