Publication Type:

Journal Article

Source:

Medical {&} Biological Engineering {&} Computing, Volume 55, Number 5, p.711–718 (2017)

URL:

http://dx.doi.org/10.1007/s11517-016-1549-y

Keywords:

Cancer diagnostics, Cell identification, High-throughput imaging, Optofluidic imaging

Abstract:

<p>Each year, about 7–8 million deaths occur due to cancer around the world. More than half of the cancer-related deaths occur in the less-developed parts of the world. Cancer mortality rate can be reduced with early detection and subsequent treatment of the disease. In this paper, we introduce a microfluidic microscopy-based cost-effective and label-free approach for identification of cancerous cells. We outline a diagnostic framework for the same and detail an instrumentation layout. We have employed classical computer vision techniques such as 2D principal component analysis-based cell type representation followed by support vector machine-based classification. Analogous to criminal face recognition systems implemented with help of surveillance cameras, a signature-based approach for cancerous cell identification using microfluidic microscopy surveillance is demonstrated. Such a platform would facilitate affordable mass screening camps in the developing countries and therefore help decrease cancer mortality rate.</p>

Cite this Research Publication

V. Kalyan Jagannadh, Gopakumar G, Subrahmanyam, G. R. K. Sai, and Gorthi, S. Siva, “Microfluidic microscopy-assisted label-free approach for cancer screening: automated microfluidic cytology for cancer screening”, Medical {&} Biological Engineering {&} Computing, vol. 55, pp. 711–718, 2017.

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