A Novel Method Based on Watershed and Transfer Learning for Recognizing Immature Precursor Cells

  • Xuehua Liu
  • , Guitao Cao*
  • , Dan Meng
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

It is an effective way to use digital image processing method to assist medical research. This paper presents a hybrid approach based on watershed and transfers learning method to automatically segment, characterize, and classify the particular immature precursor (IP) cells in bone marrow pathological (BMP) images. In segmentation phase, we use adaptive morphological reconstruction to accentuate the cell shapes and use improved marker-controlled watershed to segment the cells. Eleven morphological and statistical features are then extracted from those samples. In classification phase, we use transfer learning method to make use of the assistant sample set and generate a strong SVM classifier. Experimental results show the proposed method has a better performance, and the result lays the foundation for study of the correlations between the IP cells in BMP images and the relapse of acute myeloid leukemia (AML).

Original languageEnglish
Title of host publicationFoundations of Intelligent Systems - Proceedings of the 8th InternationalConference on Intelligent Systems and Knowledge Engineering, ISKE 2013
PublisherSpringer Verlag
Pages405-416
Number of pages12
ISBN (Print)9783642549236
DOIs
StatePublished - 2014
Event8th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2013 - Shenzhen, China
Duration: 20 Nov 201323 Nov 2013

Publication series

NameAdvances in Intelligent Systems and Computing
Volume277
ISSN (Print)2194-5357

Conference

Conference8th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2013
Country/TerritoryChina
CityShenzhen
Period20/11/1323/11/13

Keywords

  • AML
  • SVM
  • Transfer learning
  • Watershed

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