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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 |
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 |
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