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Cited by 147AI in cancer detectionCell Image Analysis TechniquesMedical Image Segmentation Techniques

NuClick: A deep learning framework for interactive segmentation of microscopic images

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Alemi Koohbanani, Navid, Jahanifar, Mostafa, Zamani Tajadin, Neda, Rajpoot, Nasir·2020·Medical Image Analysis
DOI 10.1016/j.media.2020.101771
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  • The human-in-the-loop approach has been demonstrated for simple ROI such as nuclei and round cells, but not for cells with complex morphologies that require full cytoplasmic segmentation.

    “This approach has been demonstrated for simple ROI such as nuclei and round cells, which allow for weak annotations such as clicks and squiggles18,19, but not for cells with complex morphologies that require full cytoplasmic segmentation.”

    From Cellpose 2.0: how to train your own model (2022) · cites this paper as [18]

    The Abstract and §2.3 describe interactive segmentation of nuclei and cells using clicks and glands using squiggles. The paper does not establish the claimed limitation for cells with complex morphologies requiring full cytoplasmic segmentation; it also reports segmentation of whole white blood cells (§4.5). (LLM, conf=0.87)

    Experimental — accuracy not yet measured

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Cited by

Sorted by citations

Authors
Alemi Koohbanani, N., Jahanifar, M., Zamani Tajadin, N., & Rajpoot, N.
Affiliations
University of Warwick (GB)
ORCID
Venue
Medical Image Analysis
Publisher
Elsevier BV
Published
2020-10
Volume
65
Pages
101771
ISSN
1361-8415 (ISSN-L)
DOI
10.1016/j.media.2020.101771
OpenAlex
W3040784645
Cited by
147
References
5
Citations by year
2026: 8 · 2025: 24 · 2024: 34 · 2023: 29 · 2022: 29 · 2021: 22 · 2020: 1
FWCI
7.96
Type
journal article
Language
en
Open access
Licence
Locations
  • Medical Image Analysis (publishedVersion)
  • PubMed (publishedVersion)
  • Warwick Research Archive Portal (University of Warwick) (acceptedVersion)
Funders
  • Medical Research Council
  • Innovate UK
  • Alan Turing Institute
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Cell Image Analysis Techniques
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
Keywords
interactive segmentation, nuclei segmentation, cell segmentation, gland segmentation, histological images, computational pathology, instance segmentation, blood smear images
MeSH terms
Deep Learning, Histological Techniques, Humans, Image Processing, Computer-Assisted

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