Header menu link for other important links
Blood cells counting by dynamic area-averaging using morphological operations to SEM images of cancerous blood cells
, D. Dawn, A. Halder
Published in Springer Verlag
Volume: 425
Pages: 267 - 272
In this paper, we describe a novel method of determining the complete blood cell count using region-based segmentation method of highly magnified images obtained from SEM. It provides an efficient way of measuring blood cell counts and it also be used to diagnose the presence of many life-threatening diseases such as leukemia, allergies etc. In many cases, mainly, due to diseases and cell longevity, the actual sizes of micron-order blood cells appear to change their sizes. Therefore, this proposed method uses dynamical averaging of red blood cell (RBC) and white blood cell (WBC) areas so that no a-priori area (fixed area of blood cell) is required. This is a significant step forward since no fixed area cut-offs are used to separate WBC and RBC. The SEMimages are preprocessed with a global threshold and then, significant noises are removed using morphological processing. Finally, the areas are separated using dynamical averaging and separately, WBC and RBC counts are computed. Experimental data are provided for different real samples of cancer patients which show encouraging results. © Springer International Publishing Switzerland 2016.
About the journal
JournalData powered by TypesetAdvances in Intelligent Systems and Computing
PublisherData powered by TypesetSpringer Verlag