Combined Detection and Segmentation of Cell Nuclei in Microscopy Images Using Deep Learning

Sundaresh Ram, Vicky T. Nguyen, Kirsten H. Limesand, Jeffrey J. Rodriguez

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

3 Scopus citations

Abstract

We propose a 3D convolutional neural network to simultaneously segment and detect cell nuclei in confocal microscopy images. Mirroring the co-dependency of these tasks, our proposed model consists of two serial components: the first part computes a segmentation of cell bodies, while the second module identifies the centers of these cells. Our model is trained end-to-end from scratch on a mouse parotid salivary gland stem cell nuclei dataset comprising 107 3D images from three independent cell preparations, each containing several hundred individual cell nuclei in 3D. In our experiments, we conduct a thorough evaluation of both detection accuracy and segmentation quality, on two different datasets. The results show that the proposed method provides significantly improved detection and segmentation accuracy compared to existing algorithms. Finally, we use a previously described test-time drop-out strategy to obtain uncertainty estimates on our predictions and validate these estimates by demonstrating that they are strongly correlated with accuracy.

Original languageEnglish (US)
Title of host publication2020 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages26-29
Number of pages4
ISBN (Electronic)9781728157450
DOIs
StatePublished - Mar 2020
Event2020 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2020 - Santa Fe, United States
Duration: Mar 29 2020Mar 31 2020

Publication series

NameProceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation
Volume2020-March

Conference

Conference2020 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2020
Country/TerritoryUnited States
CitySanta Fe
Period3/29/203/31/20

Keywords

  • Cell nucleus detection
  • confocal microscopy
  • convolutional neural networks
  • deep learning
  • image segmentation

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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