Abnormal shape segmentation of red blood cell using image processing / Nur Raihan Ja'afar ... [et al.]

• Main Authors: Ja'afar, Nur Raihan (Author), Zainol Abidin, Siti Nazifah (Author), Abu Mangshor, Nur Nabilah (Author), Abdul Kadir, Siti Aisyah (Author), Ahmad Zukri, Nurul Hidayah (Author)
• Format: Book
• Published: Universiti Teknologi MARA, Perak, 2019-06.
• Subjects: Article; PeerReviewed
• Online Access: Link Metadata
• Notes: https://ir.uitm.edu.my/id/eprint/39628/1/39628.pdf
• Keywords: Analysis; Algorithms

A healthy red blood cell functions to transfer oxygen from lungs to tissues and organ. The biconcave-disc shape of red blood cell maximizes the surface area to increase efficiency of oxygen absorption. Otherwise it is considered as abnormal which leads to blood disorder. Identification of blood disorders often starts with a complete blood count and supplemented by an examination of blood cells under a microscope. Some health centers provide additional tests and imaging procedures to further diagnosis. High cost of advanced instruments and expertise brings to diagnosis using existence tools which maybe imprecise, inconsistent and has low reliability. Therefore, a system using technique of image processing is proposed to segment the abnormal shape of red blood cells. Thresholding morphological operation and segmentation using morphological watershed transformation was applied in this study. The thresholding is the pre-processing method in eliminating unintended figures, while morphological operation and morphological watershed transformation are processing methods where segmentation of the abnormal shape of red blood cell is performed. The amount of red blood cell images tested in this system was 40 images. The result of the system is the segmented image of abnormal red blood cells. The accuracy rate of the resulted segmented image is 48.124%. This study is hoped to be useful in identification of abnormality of red blood cells for medical experts.