Fast and robust segmentation of white blood cell images by self-supervised learning-Reference-Cited by-同舟云学术

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Fast and robust segmentation of white blood cell images by self-supervised learning

Published:2018-04 Issue: Volume:107 Page:55-71
ISSN:0968-4328
Container-title:Micron
language:en
Short-container-title:Micron

Author:

Zheng Xin,Wang Yong,Wang Guoyou,Liu Jianguo

Funder

Key University Natural Science Research Project of Anhui Province of China

Foundation of University Research and Innovation Platform Team for Intelligent Perception and Computing of Anhui Province

Publisher

Elsevier BV

Subject

Cell Biology,Structural Biology,General Physics and Astronomy,General Materials Science

Reference35 articles.

1. Contour detection and hierarchical image segmentation;Arbeláez;IEEE Trans. Pattern Anal. Mach. Intell.,2011

2. A color and shape based algorithm for segmentation of white blood cells in peripheral blood and bone marrow images;Arslan;Cytometry,2014

3. Leukocyte nucleus segmentation and nucleus lobe counting;Chan;BMC Bioinf.,2010

4. An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods;Cristianini,2000

5. White blood cell segmentation using morphological operators and scale-space analysis;Dorini;Computer Graphics and Image Processing, 2007. XX Brazilian Symposium on. IEEE,2007

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