Sickle Blood Cell Detection Based on Image Segmentation

Author

Kholoud Alotaibi, South Dakota State UniversityFollow

Document Type

Thesis - Open Access

Award Date

2016

Degree Name

Master of Science (MS)

Department / School

Electrical Engineering and Computer Science

First Advisor

Sung Shin

Abstract

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.

Library of Congress Subject Headings

Blood cells.

Erythrocytes.

Sickle cell anemia.

Image segmentation.

Description

Includes bibliographical references (pages 78-79)

Format

application/pdf

Number of Pages

95

Publisher

South Dakota State University

Recommended Citation

Alotaibi, Kholoud, "Sickle Blood Cell Detection Based on Image Segmentation" (2016). Electronic Theses and Dissertations. 1116.
https://openprairie.sdstate.edu/etd/1116