{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T01:12:18Z","timestamp":1760231538383,"version":"build-2065373602"},"reference-count":43,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2022,9,23]],"date-time":"2022-09-23T00:00:00Z","timestamp":1663891200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["82130069","2019YFA0707004"],"award-info":[{"award-number":["82130069","2019YFA0707004"]}]},{"name":"the National Key Research and Development Program of China","award":["82130069","2019YFA0707004"],"award-info":[{"award-number":["82130069","2019YFA0707004"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Thermal inkjet printing can generate more than 300,000 droplets of picoliter scale within one second stably, and the image analysis workflow is used to quantify the positive and negative values of the droplets. In this paper, the SimpleBlobDetector detection algorithm is used to identify and localize droplets with a volume of 24 pL in bright field images and suppress bright spots and scratches when performing droplet location identification. The polynomial surface fitting of the pixel grayscale value of the fluorescence channel image can effectively compensate and correct the image vignetting caused by the optical path, and the compensated fluorescence image can accurately classify positive and negative droplets by the k-means clustering algorithm. 20 \u00b5L of the sample solution in the result reading chip can produce more than 100,000 effective droplets. The effective droplet identification correct rate of 20 images of random statistical samples can reach more than 99% and the classification accuracy of positive and negative droplets can reach more than 98% on average. This paper overcomes the problem of effectively classifying positive and negative droplets caused by the poor image quality of photographed picolitre ddPCR droplets caused by optical hardware limitations.<\/jats:p>","DOI":"10.3390\/s22197222","type":"journal-article","created":{"date-parts":[[2022,9,26]],"date-time":"2022-09-26T03:34:17Z","timestamp":1664163257000},"page":"7222","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Image Segmentation and Quantification of Droplet dPCR Based on Thermal Bubble Printing Technology"],"prefix":"10.3390","volume":"22","author":[{"given":"Mingjie","family":"Zhu","sequence":"first","affiliation":[{"name":"School of Microelectronics, Shanghai University, Shanghai 200444, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zilong","family":"Shan","sequence":"additional","affiliation":[{"name":"School of Microelectronics, Shanghai University, Shanghai 200444, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Ning","sequence":"additional","affiliation":[{"name":"Shanghai Industrial \u00b5Technology Research Institute, Shanghai 201800, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuanye","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Microelectronics, Shanghai University, Shanghai 200444, China"},{"name":"Shanghai Industrial \u00b5Technology Research Institute, Shanghai 201800, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1259","DOI":"10.1080\/22221751.2020.1772678","article-title":"ddPCR: A more accurate tool for SARS-CoV-2 detection in low viral load specimens","volume":"9","author":"Suo","year":"2020","journal-title":"Emerg. Microbes Infect."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"20200082","DOI":"10.1002\/VIW.20200082","article-title":"Applications of digital PCR in COVID-19 pandemic","volume":"2","author":"Tan","year":"2021","journal-title":"View"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/j.ymeth.2021.07.005","article-title":"Absolute quantification of SARS-CoV-2 with Clarity Plus\u2122 digital PCR","volume":"201","author":"Tan","year":"2022","journal-title":"Methods"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"958","DOI":"10.1093\/clinchem\/hvaa104","article-title":"Noninvasive Fetal Genotyping by Droplet Digital PCR to Identify Maternally Inherited Monogenic Diabetes Variants","volume":"66","author":"Caswell","year":"2020","journal-title":"Clin. Chem."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"17020","DOI":"10.1021\/acs.analchem.1c03527","article-title":"Virtual-Partition Digital PCR for High-Precision Chromosomal Counting Applications","volume":"93","author":"Jacky","year":"2021","journal-title":"Anal. Chem."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1121","DOI":"10.1002\/rth2.12425","article-title":"Detection of mosaics in hemophilia A by deep Ion Torrent sequencing and droplet digital PCR","volume":"4","author":"Manderstedt","year":"2020","journal-title":"Res. Pract. Thromb. Haemost."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"82","DOI":"10.3892\/br.2021.1458","article-title":"Droplet-based digital PCR for non-invasive prenatal genetic diagnosis of alpha and beta-thalassemia","volume":"15","author":"Sawakwongpra","year":"2021","journal-title":"Biomed. Rep."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1007\/s40291-021-00562-2","article-title":"Current and Emerging Applications of Droplet Digital PCR in Oncology: An Updated Review","volume":"26","year":"2022","journal-title":"Mol. Diagn. Ther."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Palacin-Aliana, I., Garcia-Romero, N., Asensi-Puig, A., Carrion-Navarro, J., Gonzalez-Rumayor, V., and Ayuso-Sacido, A. (2021). Clinical Utility of Liquid Biopsy-Based Actionable Mutations Detected via ddPCR. Biomedicines, 9.","DOI":"10.3390\/biomedicines9080906"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"104822","DOI":"10.1016\/j.jcv.2021.104822","article-title":"Clinical validation of a quantitative HIV-1 DNA droplet digital PCR assay: Applications for detecting occult HIV-1 infection and monitoring cell-associated HIV-1 dynamics across different subtypes in HIV-1 prevention and cure trials","volume":"139","author":"Powell","year":"2021","journal-title":"J. Clin. Virol."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Quan, P.-L., Sauzade, M., and Brouzes, E. (2018). dPCR: A Technology Review. Sensors, 18.","DOI":"10.3390\/s18041271"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"3717","DOI":"10.1039\/C8LC00990B","article-title":"Digital polymerase chain reaction technology\u2014Recent advances and future perspectives","volume":"18","author":"Sreejith","year":"2018","journal-title":"Lab Chip"},{"key":"ref_13","first-page":"581","article-title":"Development and Application of Digital PCR Technology","volume":"32","author":"Li","year":"2020","journal-title":"Prog. Chem."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1003","DOI":"10.1021\/ac202578x","article-title":"Evaluation of a Droplet Digital Polymerase Chain Reaction Format for DNA Copy Number Quantification","volume":"84","author":"Pinheiro","year":"2012","journal-title":"Anal. Chem."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1373\/clinchem.2019.304048","article-title":"Digital PCR-An Emerging Technology with Broad Applications in Microbiology","volume":"66","author":"Salipante","year":"2020","journal-title":"Clin. Chem."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.scib.2020.07.030","article-title":"Thriving microfluidic technology","volume":"66","author":"Wang","year":"2021","journal-title":"Sci. Bull."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"649","DOI":"10.1038\/nmeth.1640","article-title":"Megapixel digital PCR","volume":"8","author":"Heyries","year":"2011","journal-title":"Nat. Methods"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"163","DOI":"10.3109\/07388551.2015.1128876","article-title":"Flow cytometry: Basic principles and applications","volume":"37","author":"Adan","year":"2017","journal-title":"Crit. Rev. Biotechnol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"3838","DOI":"10.1039\/c1lc20561g","article-title":"1-Million droplet array with wide-field fluorescence imaging for digital PCR","volume":"11","author":"Hatch","year":"2011","journal-title":"Lab Chip"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"3410","DOI":"10.1039\/C9AY01005J","article-title":"A novel method based on a Mask R-CNN model for processing dPCR images","volume":"11","author":"Hu","year":"2019","journal-title":"Anal. Methods"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"3742","DOI":"10.1039\/D1LC00532D","article-title":"A rapid nucleic acid concentration measurement system with large field of view for a droplet digital PCR microfluidic chip","volume":"21","author":"Shen","year":"2021","journal-title":"Lab Chip"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Gale, B.K., Jafek, A.R., Lambert, C.J., Goenner, B.L., Moghimifam, H., Nze, U.C., and Kamarapu, S.K. (2018). A Review of Current Methods in Microfluidic Device Fabrication and Future Commercialization Prospects. Inventions, 3.","DOI":"10.3390\/inventions3030060"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1337","DOI":"10.1038\/s41587-020-0560-x","article-title":"Rapid image deconvolution and multiview fusion for optical microscopy","volume":"38","author":"Guo","year":"2020","journal-title":"Nat. Biotechnol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1109\/MSP.2006.1628876","article-title":"Deconvolution methods for 3-D fluorescence microscopy images","volume":"23","author":"Sarder","year":"2006","journal-title":"IEEE Signal Process. Mag."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"80716","DOI":"10.1109\/ACCESS.2020.2988796","article-title":"Unsupervised K-Means Clustering Algorithm","volume":"8","author":"Sinaga","year":"2020","journal-title":"IEEE Access"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"770","DOI":"10.1016\/j.bios.2015.07.016","article-title":"A microfluidic droplet digital PCR for simultaneous detection of pathogenic Escherichia coli O157 and Listeria monocytogenes","volume":"74","author":"Bian","year":"2015","journal-title":"Biosens. Bioelectron."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"130678","DOI":"10.1016\/j.snb.2021.130678","article-title":"A low-cost, programmable, and multi-functional droplet printing system for low copy number SARS-CoV-2 digital PCR determination","volume":"348","author":"Bu","year":"2021","journal-title":"Sens. Actuators B-Chem."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Meng, X., Yu, Y., and Jin, G. (2021). Numerical Simulation and Experimental Verification of Droplet Generation in Microfluidic Digital PCR Chip. Micromachines, 12.","DOI":"10.3390\/mi12040409"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"120680","DOI":"10.1016\/j.talanta.2019.120680","article-title":"Droplet digital PCR enabled by microfluidic impact printing for absolute gene quantification","volume":"211","author":"Pan","year":"2020","journal-title":"Talanta"},{"key":"ref_30","unstructured":"(2022, August 10). OpenCV SimpleBlobDetector. Available online: https:\/\/learnopencv.com\/blob-detection-using-opencv-python-c\/."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"889","DOI":"10.1369\/0022155414554835","article-title":"New Automated Single-Cell Technique for Segmentation and Quantitation of Lipid Droplets","volume":"62","author":"Dejgaard","year":"2014","journal-title":"J. Histochem. Cytochem."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Huang, J.Y., Lee, S.S., and Hsu, Y.H. (2017, January 30\u201331). Development of an imaging method for quantifying a large digital PCR droplet. Proceedings of the Conference on Optical Diagnostics and Sensing XVII\u2014Toward Point-of-Care Diagnostics, San Francisco, CA, USA.","DOI":"10.1117\/12.2251801"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"22625","DOI":"10.1021\/acsomega.1c02664","article-title":"Investigation of Different Free Image Analysis Software for High-Throughput Droplet Detection","volume":"6","author":"Sanka","year":"2021","journal-title":"ACS Omega"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1016\/j.cherd.2020.12.010","article-title":"In-process analysis of pharmaceutical emulsions using computer vision and artificial intelligence","volume":"166","author":"Unnikrishnan","year":"2021","journal-title":"Chem. Eng. Res. Des."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Anees, V.M., and Kumar, G.S. (2017, January 14\u201316). Direction estimation of crowd flow in surveillance videos. Proceedings of the 2017 IEEE Region 10 Symposium (TENSYMP), Cochin, India.","DOI":"10.1109\/TENCONSpring.2017.8070040"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Mishra, R.K., and Jain, P. (2016, January 20\u201321). A system on chip based serial number identification using computer vision. Proceedings of the 2016 IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT), Bangalore, India.","DOI":"10.1109\/RTEICT.2016.7807827"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1046\/j.1365-2818.2000.00669.x","article-title":"Retrospective shading correction based on entropy minimization","volume":"197","author":"Likar","year":"2000","journal-title":"J. Microsc."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"778","DOI":"10.3788\/YJYXS20193408.0778","article-title":"Vignetting compensation in the collection process of LED display camera","volume":"34","author":"Wang","year":"2019","journal-title":"Chin. J. Liq. Cryst. Disp."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"2243","DOI":"10.1109\/TPAMI.2008.263","article-title":"Single-Image Vignetting Correction","volume":"31","author":"Zheng","year":"2009","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"400","DOI":"10.1016\/j.rse.2012.04.001","article-title":"Inter-comparison of four models for smoothing satellite sensor time-series data to estimate vegetation phenology","volume":"123","author":"Atkinson","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1287","DOI":"10.1007\/s11432-010-4005-x","article-title":"Cubic surface fitting to image by combination","volume":"53","author":"Li","year":"2010","journal-title":"Sci. China-Inf. Sci."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Mieloch, K., Mihailescu, P., and Munk, A. (2005, January 28\u201329). Dynamic threshold using polynomial surface regression with application to the binarisation of fingerprints. Proceedings of the Conference on Biometric Technology for Human Identification II, Orlando, FL, USA.","DOI":"10.1117\/12.603377"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"4773","DOI":"10.1007\/s11227-017-2046-2","article-title":"Unsupervised text feature selection technique based on hybrid particle swarm optimization algorithm with genetic operators for the text clustering","volume":"73","author":"Abualigah","year":"2017","journal-title":"J. Supercomput."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/19\/7222\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:38:21Z","timestamp":1760143101000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/19\/7222"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,23]]},"references-count":43,"journal-issue":{"issue":"19","published-online":{"date-parts":[[2022,10]]}},"alternative-id":["s22197222"],"URL":"https:\/\/doi.org\/10.3390\/s22197222","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2022,9,23]]}}}