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

• Main Authors: ZHENG, Xin, WANG, Yong, WANG, Guoyou, LIU, Jianguo
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2018
• Subjects: Cell segmentation; Self-supervised learning; Support vector machine; White blood cell; Automatic labeling of training data; Health Information Technology; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/5884; https://ink.library.smu.edu.sg/context/sis_research/article/6885/viewcontent/miron_2018___pv.pdf
• Institution: Singapore Management University

A fast and accurate white blood cell (WBC) segmentation remains a challenging task, as different WBCs vary significantly in color and shape due to cell type differences, staining technique variations and the adhesion between the WBC and red blood cells. In this paper, a self-supervised learning appr...