Skip to main navigation Skip to search Skip to main content

Segmentation of overlapping cervical nuclei based on the identification

  • Zhao Jing
  • , Xie Yining
  • , Lu Yu
  • , He Yongjun*
  • *Corresponding author for this work
  • Harbin University of Science and Technology

Research output: Contribution to journalArticlepeer-review

Abstract

Image segmentation directly determines the performance of automatic screening technique. However, there are overlapping nuclei in nuclei images. It raises a challenge to nuclei segmentation. To solve the problem, a segmentation method of overlapping cervical nuclei based on the identification is proposed. This method consists of three stages: classifier training, recognition and fine segmentation. In the classifier training, feature selection and classifier selection are used to obtain a classifier with high recognition rate. In the recognition, the outputs of the rough segmentation are classified and processed according to their labels. In the fine segmentation, the severely overlapping nuclei are further segmented based on the prior knowledge provided by the recognition. Experiments show that this method can accurately segment overlapping nuclei.

Original languageEnglish
Pages (from-to)83-92
Number of pages10
JournalJournal of China Universities of Posts and Telecommunications
Volume25
Issue number5
DOIs
StatePublished - Oct 2018
Externally publishedYes

Keywords

  • Deep learning
  • Overlapping nuclei segmentation
  • Pits detection
  • Segmentation strategy

Fingerprint

Dive into the research topics of 'Segmentation of overlapping cervical nuclei based on the identification'. Together they form a unique fingerprint.

Cite this