Spatial-Temporal Mitosis Detection in Phase-Contrast Microscopy via Likelihood Map Estimation by 3DCNN

Kazuya Nishimura, Ryoma Bise

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

Abstract

Automated mitotic detection in time-lapse phase-contrast microscopy provides us much information for cell behavior analysis, and thus several mitosis detection methods have been proposed. However, these methods still have two problems; 1) they cannot detect multiple mitosis events when there are closely placed. 2) they do not consider the annotation gaps, which may occur since the appearances of mitosis cells are very similar before and after the annotated frame. In this paper, we propose a novel mitosis detection method that can detect multiple mitosis events in a candidate sequence and mitigate the human annotation gap via estimating spatial-temporal likelihood map by 3DCNN. In this training, the loss gradually decreases with the gap size between ground-truth and estimation. This mitigates the annotation gaps. Our method outperformed the compared methods in terms of F1-score using challenging dataset that contains the data under four different conditions. Code is publicly available in https://github.com/naivete5656/MDMLM.

Original languageEnglish
Title of host publication42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publicationEnabling Innovative Technologies for Global Healthcare, EMBC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1811-1815
Number of pages5
ISBN (Electronic)9781728119908
DOIs
Publication statusPublished - Jul 2020
Event42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020 - Montreal, Canada
Duration: Jul 20 2020Jul 24 2020

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2020-July
ISSN (Print)1557-170X

Conference

Conference42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020
CountryCanada
CityMontreal
Period7/20/207/24/20

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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