Three Dimensional Nuclei Segmentation and Classification of Fluorescence Microscopy Images

Shuo Han, Soonam Lee, Alain Chen, Changye Yang, Paul Salama, Kenneth W. Dunn, Edward J. Delp

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Segmentation and classification of cell nuclei in fluorescence 3D microscopy image volumes are fundamental steps for image analysis. However, accurate cell nuclei segmentation and detection in microscopy image volumes are hampered by poor image quality, crowding of nuclei, and large variation in nuclei size and shape. In this paper, we present an unsupervised volume to volume translation approach adapted from the Recycle-GAN using modified Hausdorff distance loss for synthetically generating nuclei with better shapes. A 3D CNN with a regularization term is used for nuclei segmentation and classification followed by nuclei boundary refinement. Experimental results demonstrate that the proposed method can successfully segment nuclei and identify individual nuclei.

Original languageEnglish (US)
Title of host publicationISBI 2020 - 2020 IEEE International Symposium on Biomedical Imaging
PublisherIEEE Computer Society
Pages526-530
Number of pages5
ISBN (Electronic)9781538693308
DOIs
StatePublished - Apr 2020
Event17th IEEE International Symposium on Biomedical Imaging, ISBI 2020 - Iowa City, United States
Duration: Apr 3 2020Apr 7 2020

Publication series

NameProceedings - International Symposium on Biomedical Imaging
Volume2020-April
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Conference

Conference17th IEEE International Symposium on Biomedical Imaging, ISBI 2020
CountryUnited States
CityIowa City
Period4/3/204/7/20

Keywords

  • convolutional neural network
  • fluorescence microscopy
  • generative adversarial network
  • nuclei segmentation

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

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  • Cite this

    Han, S., Lee, S., Chen, A., Yang, C., Salama, P., Dunn, K. W., & Delp, E. J. (2020). Three Dimensional Nuclei Segmentation and Classification of Fluorescence Microscopy Images. In ISBI 2020 - 2020 IEEE International Symposium on Biomedical Imaging (pp. 526-530). [9098560] (Proceedings - International Symposium on Biomedical Imaging; Vol. 2020-April). IEEE Computer Society. https://doi.org/10.1109/ISBI45749.2020.9098560