Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/11261
Title: Label-free detection of rare cancer cells using deep learning and magnetic levitation principle
Authors: Delikoyun, Kerem
Demir, Ali Aslan
Tekin, Hüseyin Cumhur
Keywords: Circulating tumor cell
Deep learning
Magnetic levitation
Object detection
Point-of-care testing
Issue Date: 2021
Publisher: SPIE
Abstract: Magnetic levitation is an effective tool for separating target cells within a heterogeneous solution by utilizing density differences among cell lines. However, magnetic levitation cannot be used to identify target cells which have similar density profile as the other cells in the solution. Therefore, accuracy of cell identification can dramatically reduce. In this study, we introduce, for the first time, the use of deep learning-based object detection approach for label-free identification of rare cancer cells within levitated cells. As a result, our novel and hybrid detection strategy could be used to identify circulating tumor cells for diagnosis and prognosis of cancer. © 2021 SPIE.
Description: The Society of Photo-Optical Instrumentation Engineers (SPIE)
Label-free Biomedical Imaging and Sensing, LBIS 2021 -- 6 March 2021 through 11 March 2021
URI: http://doi.org/10.1117/12.2572908
https://hdl.handle.net/11147/11261
ISBN: 9781510641457
ISSN: 1605-7422
Appears in Collections:Bioengineering / Biyomühendislik
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Show full item record



CORE Recommender

Page view(s)

3,810
checked on Feb 26, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.