| Literature DB >> 25459053 |
Mohendra Roy1, Dongmin Seo1, Chang-Hyun Oh1, Myung-Hyun Nam2, Young Jun Kim3, Sungkyu Seo4.
Abstract
Recent advances in lens-free shadow imaging technology have enabled a new class of cell imaging platform, which is a suitable candidate for point-of-care facilities. In this paper, we firstly demonstrate a compact and low-cost telemedicine device providing automated cell and particle size measurement based on lens-free shadow imaging technology. Using the generated shadow (or diffraction) patterns, the proposed approach can detect and measure the sizes of more than several hundreds of micro-objects simultaneously within a single digital image frame. In practical experiments, we defined four types of shadow parameters extracted from each micro-object shadow pattern, and found that a specific shadow parameter (peak-to-peak distance, PPD) demonstrated a linear relationship with the actual micro-object sizes. By using this information, a new algorithm suitable for operation on both a personal computer (PC) and a cell phone was also developed, providing automated size detection of poly-styrenemicro-beads and biological cells such as red blood cells, MCF-7, HepG2, and HeLa. Results from the proposed device were compared with those of a conventional optical microscope, demonstrating good agreement between two approaches. In contrast to other existing cell and particle size measurement approaches, such as Coulter counter, flow-cytometer, particle-size analyzer, and optical microscope, this device can provide accurate cell and particle size information with a 2 µm maximum resolution, at almost no cost (less than 100 USD), within a compact instrumentation size (9.3×9.0×9.0 cm(3)), and in a rapid manner (within 1 min). The proposed lens-free automated particle and cell size measurement device, based on shadow imaging technology, can be utilized as a powerful tool for many cell and particle handling procedures, including environmental, pharmaceutical, biological, and clinical applications.Keywords: CMOS image sensor; Cell size measurement; Diffraction; Lens-free imaging; Shadow
Mesh:
Year: 2014 PMID: 25459053 DOI: 10.1016/j.bios.2014.10.040
Source DB: PubMed Journal: Biosens Bioelectron ISSN: 0956-5663 Impact factor: 10.618