An image-to-answer algorithm for fully automated digital PCR image processing

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dc.contributor.authorYan, Zhiqiangcs
dc.contributor.authorZhang, Haoqingcs
dc.contributor.authorWang, Xinlucs
dc.contributor.authorGaňová, Martinacs
dc.contributor.authorLednický, Tomášcs
dc.contributor.authorZhu, Hanliangcs
dc.contributor.authorLiu, Xiaochengcs
dc.contributor.authorKorabečná, Mariecs
dc.contributor.authorChang, Honglongcs
dc.contributor.authorNeužil, Pavelcs
dc.coverage.issue7cs
dc.coverage.volume22cs
dc.date.issued2022-03-29cs
dc.description.abstractThe digital polymerase chain reaction (dPCR) is an irreplaceable variant of PCR techniques due to its capacity for absolute quantification and detection of rare deoxyribonucleic acid (DNA) sequences in clinical samples. Image processing methods, including micro-chamber positioning and fluorescence analysis, determine the reliability of the dPCR results. However, typical methods demand high requirements for the chip structure, chip filling, and light intensity uniformity. This research developed an image-to-answer algorithm with single fluorescence image capture and known image-related error removal. We applied the Hough transform to identify partitions in the images of dPCR chips, the 2D Fourier transform to rotate the image, and the 3D projection transformation to locate and correct the positions of all partitions. We then calculated each partition's average fluorescence amplitudes and generated a 3D fluorescence intensity distribution map of the image. We subsequently corrected the fluorescence non-uniformity between partitions based on the map and achieved statistical results of partition fluorescence intensities. We validated the proposed algorithms using different contents of the target DNA. The proposed algorithm is independent of the dPCR chip structure damage and light intensity non-uniformity. It also provides a reliable alternative to analyze the results of chip-based dPCR systems.en
dc.formattextcs
dc.format.extent1333-1343cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationLAB ON A CHIP. 2022, vol. 22, issue 7, p. 1333-1343.en
dc.identifier.doi10.1039/d1lc01175hcs
dc.identifier.issn1473-0189cs
dc.identifier.orcid0000-0003-0564-1862cs
dc.identifier.other179279cs
dc.identifier.urihttp://hdl.handle.net/11012/209181
dc.language.isoencs
dc.publisherROYAL SOC CHEMISTRYcs
dc.relation.ispartofLAB ON A CHIPcs
dc.relation.urihttps://pubs.rsc.org/en/content/articlelanding/2022/LC/D1LC01175Hcs
dc.rightsCreative Commons Attribution 3.0 Unportedcs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/1473-0189/cs
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/cs
dc.subjectABSOLUTE QUANTIFICATIONen
dc.subjectMICROFLUIDIC CHIPen
dc.subjectDNAen
dc.subjectDPCRen
dc.subjectMODELen
dc.subjectARRAYen
dc.titleAn image-to-answer algorithm for fully automated digital PCR image processingen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
sync.item.dbidVAV-179279en
sync.item.dbtypeVAVen
sync.item.insts2025.02.03 15:50:14en
sync.item.modts2025.01.17 15:13:33en
thesis.grantorVysoké učení technické v Brně. Středoevropský technologický institut VUT. Chytré nanonástrojecs
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