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A multivariate shape quantification approach for sickle red blood cell in patient-specific microscopy image data
Author(s): Mengjia Xu; Jinzhu Yang; Hong Zhao
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Paper Abstract

The morphological change of red blood cells(RBCs) plays an important role in revealing the biomechanical and biorheological characteristics of RBCs. Aiming to extract the shape indices for the sickle RBCs, an automated ex-vivo RBC shape quantification method is proposed. First, single RBC regions (ROIs) are extracted from raw microscopy image via an automatic hierarchical ROI extraction method. Second, an improved random walk method is used to detect the RBC outline. Finally, three types of RBC shape factors are calculated based on the elliptical fitting RBC contour. Experiments indicate that the proposed method can accurately segment the RBCs from the microscopy images with low contrast and prevent the disturbance of artifacts. Moreover, it can provide an efficient shape quantification means for diverse RBC shapes in a batch manner.

Paper Details

Date Published: 21 July 2017
PDF: 6 pages
Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 104203W (21 July 2017); doi: 10.1117/12.2281565
Show Author Affiliations
Mengjia Xu, Northeastern Univ. (China)
Brown Univ. (United States)
Jinzhu Yang, Northeastern Univ. (China)
Hong Zhao, Northeastern Univ. (China)


Published in SPIE Proceedings Vol. 10420:
Ninth International Conference on Digital Image Processing (ICDIP 2017)
Charles M. Falco; Xudong Jiang, Editor(s)

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