@inproceedings{71848b49d68f46b390cbfa056c48e4da,
title = "A multivariate shape quantification approach for sickle red blood cell in patient-specific microscopy image data",
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.",
keywords = "Sickle cell disease, batch processing, cell contour detection, microscopy image, shape analysis",
author = "Mengjia Xu and Jinzhu Yang and Hong Zhao",
note = "Publisher Copyright: {\textcopyright} 2017 SPIE.; 9th International Conference on Digital Image Processing, ICDIP 2017 ; Conference date: 19-05-2017 Through 22-05-2017",
year = "2017",
doi = "10.1117/12.2281565",
language = "English (US)",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Xudong Jiang and Falco, {Charles M.}",
booktitle = "Ninth International Conference on Digital Image Processing, ICDIP 2017",
address = "United States",
}