Classification of anemia severity from real-life conjunctival images

Huang, Bryan

Permalink

https://hdl.handle.net/2142/122115 Copy

Description

Title

Classification of anemia severity from real-life conjunctival images

Author(s)

Huang, Bryan

Issue Date

2023-12-07

Director of Research (if dissertation) or Advisor (if thesis)

Ahuja, Narendra

Department of Study

Electrical & Computer Eng

Discipline

Electrical & Computer Engr

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Keyword(s)

• Image processing
• conjunctiva
• anemia

Abstract

Once anemia has been identified in a patient, its severity is a significant factor in planning treatment. Images of the palpebral conjunctiva have been shown to be accurate in assessing a patient’s hemoglobin concentration without the need to draw blood. In this work, we aim to demonstrate the efficacy of these methods in assessment in real conditions, using consumer-grade equipment. We apply vessel segmentation methods and a linear color mixing model to estimate the color of blood, and, then, use that color to classify anemia severity. Our results indicate that these methods can classify anemia severity at a similar level to human clinicians using a color scale on drawn blood, using images taken in a real-life hospital setting. Additionally, we review conditions and limitations unique to the task of assessing the severity of anemia.

Graduation Semester

2023-12

Type of Resource

Thesis

Handle URL

https://hdl.handle.net/2142/122115

Copyright and License Information

Copyright 2023 Bryan Huang

Owning Collections