Identification of Abnormalities in Head Computerized Tomography Scans

M. Delrocini, C. Angelini, G. Rasool

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Stroke and traumatic brain injuries are both leading causes of death and long-term disability globally [1]. Early detection of abnormalities in head computerized tomography (CT) scans reduces patient risk of serious medical complications from brain injuries such as hemorrhagic stroke and cranial fractures [2]. A machine learning algorithm trained to autonomously identify and classify head CT scan irregularities has the potential to decrease detection time of such anomalies and allow for quicker, more effective treatment.

Original languageEnglish (US)
Title of host publication2020 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728188201
DOIs
StatePublished - Dec 5 2020
Event2020 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2020 - Philadelphia, United States
Duration: Dec 5 2020 → …

Publication series

Name2020 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2020 - Proceedings

Conference

Conference2020 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2020
Country/TerritoryUnited States
CityPhiladelphia
Period12/5/20 → …

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Mechanical Engineering
  • Safety, Risk, Reliability and Quality
  • Control and Optimization
  • Health Informatics

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