Please use this identifier to cite or link to this item:
|Title:||Robust contour reconstruction of red blood cells and parasites in the automated identification of the stages of malarial infection|
Support vector machine
|Citation:||Kumarasamy, S.K., Ong, S.H., Tan, K.S.W. (2011-05). Robust contour reconstruction of red blood cells and parasites in the automated identification of the stages of malarial infection. Machine Vision and Applications 22 (3) : 461-469. ScholarBank@NUS Repository. https://doi.org/10.1007/s00138-010-0284-x|
|Abstract:||We present a novel method for detecting malaria parasites and determining the stage of infection from digital images comprising red blood cells (RBCs). The proposed method is robust under varying conditions of image luminance, contrast and clumping of RBCs. Both strong and weak boundary edges of the RBCs and parasites are detected based on the similarity measure between local image neighborhoods and predefined edge filters. A rule-based algorithm is applied to link edge fragments to form closed contours of the RBCs and parasite regions, as well as to split clumps into constituent cells. A radial basis support vector machine determines the stage of infection from features extracted from each parasite region. The proposed method achieves 97% accuracy in cell segmentation and 86% accuracy in parasite detection when tested on a total of 530 digitally captured images of three species of malaria parasites: Plasmodium falciparum, Plasmodium yoelii and Plasmodium berghei. © Springer-Verlag 2010.|
|Source Title:||Machine Vision and Applications|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Oct 20, 2018
WEB OF SCIENCETM
checked on Oct 3, 2018
checked on Oct 6, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.