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Proceedings Paper

Dendritic cell recognition using template matching based on one-dimensional (1D) Fourier descriptors (FD)
Author(s): Anis Azwani Muhd Suberi; Wan Nurshazwani Wan Zakaria; Razali Tomari; Mei Xia Lau
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Paper Abstract

Identification of Dendritic Cell (DC) particularly in the cancer microenvironment is a unique disclosure since fighting tumor from the harnessing immune system has been a novel treatment under investigation. Nowadays, the staining procedure in sorting DC can affect their viability. In this paper, a computer aided system is proposed for automatic classification of DC in peripheral blood mononuclear cell (PBMC) images. Initially, the images undergo a few steps in preprocessing to remove uneven illumination and artifacts around the cells. In segmentation, morphological operators and Canny edge are implemented to isolate the cell shapes and extract the contours. Following that, information from the contours are extracted based on Fourier descriptors, derived from one dimensional (1D) shape signatures. Eventually, cells are classified as DC by comparing template matching (TM) of established template and target images. The results show that the proposed scheme is reliable and effective to recognize DC.

Paper Details

Date Published: 11 July 2016
PDF: 5 pages
Proc. SPIE 10011, First International Workshop on Pattern Recognition, 100110K (11 July 2016); doi: 10.1117/12.2242814
Show Author Affiliations
Anis Azwani Muhd Suberi, Univ. Tun Hussein Onn Malaysia (Malaysia)
Wan Nurshazwani Wan Zakaria, Univ. Tun Hussein Onn Malaysia (Malaysia)
Razali Tomari, Univ. Tun Hussein Onn Malaysia (Malaysia)
Mei Xia Lau, Univ. Tun Hussein Onn Malaysia (Malaysia)


Published in SPIE Proceedings Vol. 10011:
First International Workshop on Pattern Recognition
Xudong Jiang; Guojian Chen; Genci Capi; Chiharu Ishll, Editor(s)

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