Sickle Blood Cell Detection Based on Image Segmentation

<p>Red blood cells have a vital role in human health. Red blood cells have a circular shape and a concave surface and exchange the gasses between the inside and outside of the body. However, at times, these normally round cells become sickle shaped, which is an indication of sickle cell disease. This paper introduces a unique approach to detect sickle blood cells in blood samples using image segmentation and shape detection. This method is based on calculating the max axis and min axis of the cell. The form factor is computed using these properties to determine whether the cell is sickle or not. This method is 90 percent more accurate than the existing method.</p>

Name thesis:degree_name

Master of Science (MS)

Level thesis:degree_level

Thesis - Open Access

Discipline thesis:degree_discipline

Electrical Engineering and Computer Science

Year dc:date.available

2016

Author dc:creator

• Alotaibi, Kholoud

Contributors dc:contributor

• Sung Shin

• Biomedical
• Computer Engineering
• Electrical and Computer Engineering

Licence

• http://rightsstatements.org/vocab/InC/1.0/

Language dc:language

en

Repository record dc:identifier

https://openprairie.sdstate.edu/etd/1116

OAI identifier oai:identifier

oai:openprairie.sdstate.edu:etd-2117