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Multi-streams and Multi-features for Cell Classification

  • Xinpeng Xie
  • Yuexiang Li
  • Menglu Zhang
  • Yong Wu
  • Linlin ShenEmail author
Conference paper
Part of the Lecture Notes in Bioengineering book series (LNBE)

Abstract

With the development of deep learning technique, cell classification has gained increasing interests from the community. Identifying malignant cells in B-ALL white blood cancer microscopic images is challenging, since the normal and malignant cells have similar appearances. Traditional cell identification approach requires experienced pathologists to carefully read the cell images, which is laborious and suffers from inter-observer variations. Hence, the computer aid diagnosis systems for blood disorders, for example, leukemia, are worthwhile to develop. In this paper, we design a multi-stream model to classify the immature leukemic blasts and normal cells. We evaluated the proposed model on the C-NMC 2019 challenge dataset. The experimental results show that a promising result is achieved by our model.

Keywords

Leukemia cell identification Deep learning network Feature fusion 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Xinpeng Xie
    • 1
  • Yuexiang Li
    • 2
  • Menglu Zhang
    • 1
  • Yong Wu
    • 1
  • Linlin Shen
    • 1
    Email author
  1. 1.Computer Vision InstituteShenzhen UniversityShenzhenChina
  2. 2.Youtu Lab, TencentShenzhenChina

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