An automated detection algorithm for lens-free imaging system
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Mohendra Roy | - |
dc.contributor.author | 서동민 | - |
dc.contributor.author | 김재우 | - |
dc.contributor.author | 오상우 | - |
dc.contributor.author | 서성규 | - |
dc.date.accessioned | 2021-12-08T14:41:13Z | - |
dc.date.available | 2021-12-08T14:41:13Z | - |
dc.date.issued | 20141206 | - |
dc.identifier.uri | https://www.kriso.re.kr/sciwatch/handle/2021.sw.kriso/4358 | - |
dc.description.abstract | Recently lens-free imaging technology has been extensively used in the micro-particle and biological cell analysis. This is due to its high throughput, low cost, simple and compact arrangement. However this technology is still lacking in dedicated automated detection system. In this paper, we describe an automated detection method, custom developed for the lens-free imaging. For that, firstly we developed a lens-free imaging system using low cost components. This system was used to generate and capture the diffraction patterns of the micro objects. These lens free images were then processed with the custom developed algorithm. The performance of this approach was evaluated by comparing the counting results with the standard optical microscope results. Thus we evaluated the counting results for four samples of polystyrene micro beads, RBC, HepG2, HeLa and MCF-7 cell lines. The comparison shows a good agreement between the systems with correlation coefficient of 0.95 and linearity slop of 0.887. This Wi-Fi enabled lens-free imaging system along with the dedicated software possesses great potential for telemedicine applications in resource limited settings.dicated automated detection system. In this paper, we describe an automated detection method, custom developed for the lens-free imaging. For that, firstly we developed a lens-free imaging system using low cost components. This system was used to generate and capture the diffraction patterns of the micro objects. These lens free images were then processed with the custom developed algorithm. The performance of this approach was evaluated by comparing the counting results with the standard optical microscope results. Thus we evaluated the counting results for four samples of polystyrene micro beads, RBC, HepG2, HeLa and MCF-7 cell lines. The comparison shows a good agreement between the systems with correlation coefficient of 0.95 and linearity slop of 0.887. This Wi-Fi enabled lens-free imaging system along with the dedicated software possesses great potential for telemedicine applications in resource limited settings. | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.title | An automated detection algorithm for lens-free imaging system | - |
dc.title.alternative | An automated detection algorithm for lens-free imaging system | - |
dc.type | Conference | - |
dc.citation.title | International Student Paper Contest | - |
dc.citation.volume | 1 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 134 | - |
dc.citation.endPage | 138 | - |
dc.citation.conferenceName | International Student Paper Contest | - |
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