Fine-grained leukocyte classification with deep residual learning for microscopic images.

Journal: Computer methods and programs in biomedicine
Published Date:

Abstract

BACKGROUND AND OBJECTIVE: Leukocyte classification and cytometry have wide applications in medical domain, previous researches usually exploit machine learning techniques to classify leukocytes automatically. However, constrained by the past development of machine learning techniques, for example, extracting distinctive features from raw microscopic images are difficult, the widely used SVM classifier only has relative few parameters to tune, these methods cannot efficiently handle fine-grained classification cases when the white blood cells have up to 40 categories.

Authors

  • Feiwei Qin
    School of Computer Science and Technology, Hangzhou Dianzi University, China. Electronic address: qinfeiwei@hdu.edu.cn.
  • Nannan Gao
    School of Computer Science and Technology, Hangzhou Dianzi University, China.
  • Yong Peng
    Department of Cardiology, West China Hospital, Sichuan University, Chengdu 610041, China.
  • Zizhao Wu
    School of Media and Design, Hangzhou Dianzi University, China.
  • Shuying Shen
    Department of Orthopaedic Surgery, Sir Run Run Shaw Hospital, China.
  • Artur Grudtsin
    School of Computer Science and Technology, Hangzhou Dianzi University, China.