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

被引：0

作者：

de Haan, Kevin ^{[1
,2
,3
]}

Koydemir, Hatice Ceylan ^{[1
,2
,3
]}

Rivenson, Yair ^{[1
,2
,3
]}

Tseng, Derek ^{[1
,2
,3
]}

Van Dyne, Elizabeth ^{[4
]}

Bakic, Lissette ^{[5
]}

Karinca, Doruk ^{[6
]}

Liang, Kyle ^{[6
]}

Ilango, Megha ^{[6
]}

Gumustekin, Esin ^{[7
]}

Ozcan, Aydogan ^{[1
,2
,3
,8
]}

机构：

[1] Univ Calif Los Angeles, David Geffen Sch Med, Elect & Comp Engn Dept, Los Angeles, CA 90095 USA

[2] Univ Calif Los Angeles, David Geffen Sch Med, Bioengn Dept, Los Angeles, CA 90095 USA

[3] Univ Calif Los Angeles, David Geffen Sch Med, Calif NanoSyst Inst CNSI, Los Angeles, CA 90095 USA

[4] Univ Calif Los Angeles, David Geffen Sch Med, Dept Pediat, Div Hematol Oncol, Los Angeles, CA 90095 USA

[5] Univ Calif Los Angeles, David Geffen Sch Med, Dept Pathol & Lab Med, Los Angeles, CA 90095 USA

[6] Univ Calif Los Angeles, David Geffen Sch Med, Dept Comp Sci, Los Angeles, CA 90095 USA

[7] Univ Calif Los Angeles, David Geffen Sch Med, Dept Neurosci, Los Angeles, CA 90095 USA

[8] Univ Calif Los Angeles, David Geffen Sch Med, Dept Surg, Los Angeles, CA 90095 USA

来源：

2020 CONFERENCE ON LASERS AND ELECTRO-OPTICS (CLEO) | 2020年

关键词：

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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. (C) 2020 The Author(s)

引用

页数：2

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