{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/122115"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/122115","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Classification of anemia severity from real-life conjunctival images","abstract":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-12-01","abstract_html":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-12-01","abstract_has_math":false,"creators":["Huang, Bryan"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Ahuja, Narendra"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2023,"date_issued":"2023-12","date_published":"2023-12","updated_at":"2026-07-22T22:25:00Z","subjects":["Image Processing","Conjunctiva","Anemia"],"languages":["en","eng"],"rights":["Copyright 2023 Bryan Huang"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/122115","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Ahuja, Narendra"]},{"key":"dc:creator","label":"Author","values":["Huang, Bryan"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2023-12","2023-12-07"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical & Computer Engr"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Image Processing","Conjunctiva","Anemia"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2023 Bryan Huang"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/122115"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["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","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."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Classification of anemia severity from real-life conjunctival images"]}]}],"canonical_facts":{"dc:contributor":["Ahuja, Narendra"],"dc:creator":["Huang, Bryan"],"dc:date":["2023-12","2023-12-07"],"dc:description":["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","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."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/122115"],"dc:language":["en","eng"],"dc:rights":["Copyright 2023 Bryan Huang"],"dc:subject":["Image Processing","Conjunctiva","Anemia"],"dc:title":["Classification of anemia severity from real-life conjunctival images"],"dc:type":["text"],"thesis:degree_discipline":["Electrical & Computer Engr"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:00Z"}