The morphological classification of normal and abnormal red blood cell using Self Organizing Map

10th International Conference Numerical Analysis in Engineering

数学;工业技术

Rahmat, R.F.^1 ; Wulandari, F.S.^1 ; Faza, S.^1 ; Muchtar, M.A.^1 ; Siregar, I.^2

Department of Information Technology, Faculty of Computer Science and Information Technology, Universitas Sumatera Utara, Medan, Indonesia^1

Department of Industrial Engineering, Faculty of Engineering, Universitas Sumatera Utara, Medan, Indonesia^2

关键词: Abnormal morphology;    Accuracy testing;    Digital image processing technologies;    Living creatures;    Morphological classifications;    Organizing map;    Red blood cell;    Self-organizing map neural network;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/308/1/012015/pdf
DOI  :  10.1088/1757-899X/308/1/012015

学科分类：工业工程学

来源: IOP

【 摘 要 】

Blood is an essential component of living creatures in the vascular space. For possible disease identification, it can be tested through a blood test, one of which can be seen from the form of red blood cells. The normal and abnormal morphology of the red blood cells of a patient is very helpful to doctors in detecting a disease. With the advancement of digital image processing technology can be used to identify normal and abnormal blood cells of a patient. This research used self-organizing map method to classify the normal and abnormal form of red blood cells in the digital image. The use of self-organizing map neural network method can be implemented to classify the normal and abnormal form of red blood cells in the input image with 93,78% accuracy testing.