Skip to main navigation Skip to search Skip to main content

Automated Screening of Sickle Cells using a Smartphone-Based Microscope and Deep Learning

  • Kevin De Haan
  • , Hatice Ceylan Koydemir
  • , Yair Rivenson
  • , Derek Tseng
  • , Elizabeth Van Dyne
  • , Lissette Bakic
  • , Doruk Karinca
  • , Kyle Liang
  • , Megha Ilango
  • , Esin Gumustekin
  • , Aydogan Ozcan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We present a deep learning-based framework for performing automatic screening of sickle cells using a smartphone-based microscope. We achieved 98% accuracy when blindly testing 96 human blood smear slides, including 32 with sickle cell disease.

Original languageEnglish
Title of host publication2020 Conference on Lasers and Electro-Optics, CLEO 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers
ISBN (Electronic)9781943580767
StatePublished - 1 May 2020
Externally publishedYes
Event2020 Conference on Lasers and Electro-Optics, CLEO 2020 - San Jose, United States
Duration: 10 May 202015 May 2020

Publication series

NameConference Proceedings - Lasers and Electro-Optics Society Annual Meeting-LEOS
Volume2020-May
ISSN (Print)1092-8081

Conference

Conference2020 Conference on Lasers and Electro-Optics, CLEO 2020
Country/TerritoryUnited States
CitySan Jose
Period10/05/2015/05/20

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Automated Screening of Sickle Cells using a Smartphone-Based Microscope and Deep Learning'. Together they form a unique fingerprint.

Cite this