University of Illinois Urbana-Champaign

Classification of anemia severity from real-life conjunctival images

Huang, Bryan

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

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
Copyright and License Information
Copyright 2023 Bryan Huang

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