2026-09-23T04:31:43Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/122115 2024-03-02 col_2142_5131 col_2142_8888 com_2142_5130 com_2142_8887 com_2142_234

Ahuja, Narendra 2023-12 application/pdf en text Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-12-01 The student, Bryan Huang, accepted the attached license on 2023-11-24 at 13:48. The student, Bryan Huang, submitted this Thesis for approval on 2023-11-24 at 13:49. This Thesis was approved for publication on 2023-12-07 at 14:53. DSpace SAF Submission Ingestion Package generated from Vireo submission #19942 on 2024-03-01 at 13:29:51 Classification of anemia severity from real-life conjunctival images Huang, Bryan Image Processing Conjunctiva Anemia 2023-12-07 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. Text eng https://hdl.handle.net/2142/122115 Copyright 2023 Bryan Huang M.S. Thesis Electrical & Computer Engr University of Illinois at Urbana-Champaign Electrical & Computer Eng