Open AccessAn Enhanced Segmentation Technique for Smokers RBC Rouleax Coin Stacking
Author(s) -
M. H. Malijan,
Johan Mohamad Sharif,
Abdul Hanan Abdullah,
M. Mahadi Abdul Jamil
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/884/1/012054
Subject(s) - stacking , segmentation , computer science , artificial intelligence , image segmentation , medicine , computer vision , biomedical engineering , chemistry , organic chemistry
Smoking is one of the major factors of having coin stacking formation of Red Blood Cell or commonly known as RBC that can cause blood clots and can lead to stroke. Smokers tends have thicker, high count, and overlapping of RBC compared to non-smokers. Blood cell detection plays significant part in biomedical field. There are two methods in detection of RBC, manual inspection by medical experts and automated machines. The manual inspection process is detection of blood cells under a microscope that is more prone to human error and time consuming, while automated hardware solutions like automated haematology machines are available, due to high cost it is not widely available to poor and developing countries who have a high statistic of smokers. Smokers have a high tendency of overlapping RBC or commonly known as rouleaux coin stacking cell formation. This study presents an enhanced segmentation technique that can detect the high degree of overlapping RBCs of smokers using digital image processing that can be helpful in the medical field.