The
study of the morphology of White Blood Cells (WBCs) further contributes to the
clinical diagnosis of blood diseases. In this research paper, we come up with
an image segmentation enhancement by combining Fourier Fast Transform on smear
blood capture and classical thresholding. The Fast Fourier Transform (FFT) is a
very powerful tool in image processing and it was used to segment and extract
the WBCs. Our image processing method uses a Fast Fourier Transform combined
with filtering and an Inverse Fast Fourier Transform for the extraction and
visualization of the high frequency region of the image. In order to remove
residual Red Blood Cells acting as noise in the expected result, a final
thresholding step is added at the end of the processing. The results presented
in this article report the tests performed using our mathematical
implementation. Moreover, we were able to detect and differentiate the
sub-families of WBCs.
References
[1]
Safuan, S.N.M., Tomari, R., Zakaria, W.N.W. and Othman, N. (2017) White Blood Cell Counting Analysis of Blood Smear Images Using Various Segmentation Strategies. AIP Conference Proceedings, 1883, Article ID: 020018. https://doi.org/10.1063/1.5002036
[2]
Ruberto, C.D., Loddo, A. and Putzu, L. (2019) Detection of Red and White Blood Cells from Microscopic Blood Images Using a Region Proposal Approach. Computers in Biology and Medicine, 116, Article ID: 103530. https://doi.org/10.1016/j.compbiomed.2019.103530
[3]
Mahmood, N.H. and Mansor, M.A. (2012) Red Blood Cells Estimation Using Hough Transform Technique. Signal & Image Processing: An International Journal (SIPIJ), 3, 53-64. https://doi.org/10.5121/sipij.2012.3204
[4]
Patil, P.R., Sable, G.S. and Anandgaonkar, G. (2019) Counting of WBCs and RBCs from Blood Images Using Gray Thresholding. International Journal of Research in Engineering and Technology, 3, 391-395.
