{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T11:10:36Z","timestamp":1780571436735,"version":"3.54.1"},"reference-count":60,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T00:00:00Z","timestamp":1638316800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["2042563"],"award-info":[{"award-number":["2042563"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Vicerrector\u00eda de Descubrimiento y Creaci\u00f3n at Universidad EAFIT","award":["NA"],"award-info":[{"award-number":["NA"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The conventional reconstruction method of off-axis digital holographic microscopy (DHM) relies on computational processing that involves spatial filtering of the sample spectrum and tilt compensation between the interfering waves to accurately reconstruct the phase of a biological sample. Additional computational procedures such as numerical focusing may be needed to reconstruct free-of-distortion quantitative phase images based on the optical configuration of the DHM system. Regardless of the implementation, any DHM computational processing leads to long processing times, hampering the use of DHM for video-rate renderings of dynamic biological processes. In this study, we report on a conditional generative adversarial network (cGAN) for robust and fast quantitative phase imaging in DHM. The reconstructed phase images provided by the GAN model present stable background levels, enhancing the visualization of the specimens for different experimental conditions in which the conventional approach often fails. The proposed learning-based method was trained and validated using human red blood cells recorded on an off-axis Mach\u2013Zehnder DHM system. After proper training, the proposed GAN yields a computationally efficient method, reconstructing DHM images seven times faster than conventional computational approaches.<\/jats:p>","DOI":"10.3390\/s21238021","type":"journal-article","created":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T01:45:02Z","timestamp":1638323102000},"page":"8021","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Video-Rate Quantitative Phase Imaging Using a Digital Holographic Microscope and a Generative Adversarial Network"],"prefix":"10.3390","volume":"21","author":[{"given":"Raul","family":"Castaneda","sequence":"first","affiliation":[{"name":"Department of Electrical and Computer Engineering, The University of Memphis, Memphis, TN 38152, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1007-5028","authenticated-orcid":false,"given":"Carlos","family":"Trujillo","sequence":"additional","affiliation":[{"name":"Applied Optics Group, Physical Sciences Department, Universidad EAFIT, Medellin 050037, Colombia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0448-376X","authenticated-orcid":false,"given":"Ana","family":"Doblas","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, The University of Memphis, Memphis, TN 38152, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"106188","DOI":"10.1016\/j.optlaseng.2020.106188","article-title":"Quantitative phase imaging trends in biomedical applications","volume":"135","author":"Cacace","year":"2020","journal-title":"Opt. Lasers Eng."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Popescu, G. (2012). Quantitative Phase Imaging of Cells and Tissues, McGraw-Hill.","DOI":"10.1364\/CLEO_SI.2012.CTu3J.5"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"578","DOI":"10.1038\/s41566-018-0253-x","article-title":"Quantitative phase imaging in biomedicine","volume":"12","author":"Park","year":"2018","journal-title":"Nat. Photonics"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2019","DOI":"10.3389\/fphy.2019.00226","article-title":"Editorial: Quantitative Phase Imaging and Its Applications to Biophysics, Biology, and Medicine","volume":"7","author":"Park","year":"2020","journal-title":"Front. Phys."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1016\/S0030-4018(96)00454-3","article-title":"Rapid quantitative phase imaging using the transport of intensity equation","volume":"133","author":"Gureyev","year":"1997","journal-title":"Opt. Commun."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1427","DOI":"10.1364\/OL.41.001427","article-title":"Real-time quantitative phase imaging based on transport of intensity equation with dual simultaneously recorded field of view","volume":"41","author":"Tian","year":"2016","journal-title":"Opt. Lett."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Mir, M., Bhaduri, B., Wang, R., Zhu, R., and Popescu, G. (2012). Quantitative Phase Imaging, Elsevier Inc.","DOI":"10.1016\/B978-0-44-459422-8.00003-5"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"4344","DOI":"10.1364\/OL.41.004344","article-title":"Quantitative phase imaging by single-shot Hilbert\u2013Huang phase microscopy","volume":"41","author":"Trusiak","year":"2016","journal-title":"Opt. Lett."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"13955","DOI":"10.1038\/s41598-020-69717-1","article-title":"Variational Hilbert Quantitative Phase Imaging","volume":"10","author":"Trusiak","year":"2020","journal-title":"Sci. Rep."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1016\/S0040-1951(98)00263-7","article-title":"Microstructural imaging techniques: A comparison between light and scanning electron microscopy","volume":"303","author":"Trimby","year":"1999","journal-title":"Tectonophysics"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"648","DOI":"10.1364\/JOSAA.5.000648","article-title":"Bright-field microscopy of semitransparent objects","volume":"5","author":"Stagaman","year":"1988","journal-title":"J. Opt. Soc. Am. A"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"30553","DOI":"10.1364\/OE.22.030553","article-title":"Phase derivative method for reconstruction of slightly off-axis digital holograms","volume":"22","author":"Guo","year":"2014","journal-title":"Opt. Express"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"35078","DOI":"10.1364\/OE.435915","article-title":"Roadmap on digital holography","volume":"29","author":"Javidi","year":"2021","journal-title":"Opt. Express"},{"key":"ref_14","first-page":"18005","article-title":"Principles and techniques of digital holographic microscopy","volume":"1","author":"Kim","year":"2010","journal-title":"SPIE Rev."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"13563","DOI":"10.1364\/OE.18.013563","article-title":"Strategies for three-dimensional particle tracking with holographic video microscopy","volume":"18","author":"Cheong","year":"2010","journal-title":"Opt. Express"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"112306","DOI":"10.1117\/1.OE.53.11.112306","article-title":"Review of digital holographic microscopy for three-dimensional profiling and tracking","volume":"53","author":"Yu","year":"2014","journal-title":"Opt. Eng."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"054032","DOI":"10.1117\/1.2357174","article-title":"Digital holographic microscopy for the three-dimensional dynamic analysis of in vitro cancer cell migration","volume":"11","author":"Dubois","year":"2006","journal-title":"J. Biomed. Opt."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"031002","DOI":"10.1088\/2515-7647\/ab8a58","article-title":"Overview of cell motility-based sickle cell disease diagnostic system in shearing digital holographic microscopy","volume":"2","author":"Anand","year":"2020","journal-title":"J. Phys. Photonics"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"14680","DOI":"10.1038\/s41598-020-71538-1","article-title":"Exploiting the potential of commercial digital holographic microscopy by combining it with 3D matrix cell culture assays","volume":"10","author":"Hellesvik","year":"2020","journal-title":"Sci. Rep."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"034005","DOI":"10.1117\/1.2204609","article-title":"Investigation of living pancreas tumor cells by digital holographic microscopy","volume":"11","author":"Kemper","year":"2006","journal-title":"J. Biomed. Opt."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"64630G","DOI":"10.1117\/12.699837","article-title":"Process engineering and failure analysis of MEMS and MOEMS by digital holography microscopy (DHM)","volume":"6463","author":"Montfort","year":"2007","journal-title":"Proc. SPIE"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"77","DOI":"10.3807\/JOSK.2010.14.2.077","article-title":"Applications of digital holography in biomedical microscopy","volume":"14","author":"Kim","year":"2010","journal-title":"J. Opt. Soc. Korea"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"A12","DOI":"10.1364\/AO.57.000A12","article-title":"Single-shot 3D topography of reflective samples with digital holographic microscopy","volume":"57","year":"2018","journal-title":"Appl. Opt."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Osten, W. (2019). Digital Holography and Its Application in MEMS\/MOEMS Inspection, CRC Press. [2nd ed.].","DOI":"10.1201\/9780429186738-14"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"46022","DOI":"10.1117\/1.JBO.19.4.046022","article-title":"Accurate single-shot quantitative phase imaging of biological specimens with telecentric digital holographic microscopy","volume":"19","author":"Doblas","year":"2014","journal-title":"J. Biomed. Opt."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"10299","DOI":"10.1364\/AO.55.010299","article-title":"Automatic full compensation of quantitative phase imaging in off-axis digital holographic microscopy","volume":"55","author":"Trujillo","year":"2016","journal-title":"Appl. Opt."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"3111","DOI":"10.1364\/BOE.7.003111","article-title":"Automated Fourier space region-recognition filtering for off-axis digital holographic microscopy","volume":"7","author":"He","year":"2016","journal-title":"Biomed. Opt. Express"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"15043","DOI":"10.1364\/OE.25.015043","article-title":"Automatic phase aberration compensation for digital holographic microscopy based on deep learning background detection","volume":"25","author":"Nguyen","year":"2017","journal-title":"Opt. Express"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"17141","DOI":"10.1038\/lsa.2017.141","article-title":"Phase recovery and holographic image reconstruction using deep learning in neural networks","volume":"7","author":"Rivenson","year":"2018","journal-title":"Light Sci. Appl."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"500","DOI":"10.1109\/JDT.2010.2052020","article-title":"Real-time digital holographic microscopy for phase contrast 3D imaging of dynamic phenomena","volume":"6","author":"Anand","year":"2010","journal-title":"IEEE\/OSA J. Disp. Technol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"A202","DOI":"10.1364\/AO.58.00A202","article-title":"Focus prediction in digital holographic microscopy using deep convolutional neural networks","volume":"58","author":"Manninen","year":"2019","journal-title":"Appl. Opt."},{"key":"ref_32","unstructured":"Pitk\u00e4aho, T., Manninen, A., and Naughton, T.J. (September, January 30). Deep convolutional neural networks and digital holographic microscopy for in-focus depth estimation of microscopic objects. Proceedings of the Irish Machine Vision and Image Processing Conference Proceedings, Maynooth, Ireland."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Liu, T., Wei, Z., Rivenson, Y., de Haan, K., Zhang, Y., Wu, Y., and Ozcan, A. (2020, January 10\u201315). Color Holographic Microscopy Using a Deep Neural Network. Proceedings of the Conference on Lasers and Electro-Optics, Optical Society of America, Washington, DC, USA.","DOI":"10.1364\/CLEO_AT.2020.AM1I.1"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"3900312","DOI":"10.1109\/JPHOT.2019.2961137","article-title":"Digital holographic reconstruction based on deep learning framework with unpaired data","volume":"12","author":"Yin","year":"2020","journal-title":"IEEE Photonics J."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1038\/s41377-019-0196-0","article-title":"Deep learning in holography and coherent imaging","volume":"8","author":"Rivenson","year":"2019","journal-title":"Light Sci. Appl."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"4765","DOI":"10.1364\/OL.44.004765","article-title":"Y-Net: A one-to-two deep learning framework for digital holographic reconstruction","volume":"44","author":"Wang","year":"2019","journal-title":"Opt. Lett."},{"key":"ref_37","first-page":"1","article-title":"Application of Deep Learning Techniques to Digital Holographic Microscopy for Numerical Reconstruction","volume":"Volume 2535","author":"Vijayanagaram","year":"2020","journal-title":"Proceedings of theAll-Russian Conference \u201cSpatial Data Processing for Monitoring of Natural and Anthropogenic Processes\u201d (SDM-2019)"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3389\/fphy.2021.651313","article-title":"Quantitative Phase Imaging Using Deep Learning-Based Holographic Microscope","volume":"9","author":"Di","year":"2021","journal-title":"Front. Phys."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"26284","DOI":"10.1364\/OE.398528","article-title":"Noise-free quantitative phase imaging in Gabor holography with conditional generative adversarial network","volume":"28","author":"Moon","year":"2020","journal-title":"Opt. Express"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"24928","DOI":"10.1364\/OE.430524","article-title":"Quantitative phase imaging in digital holographic microscopy based on image inpainting using a two-stage generative adversarial network","volume":"29","author":"Ma","year":"2021","journal-title":"Opt. Express"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"6994","DOI":"10.1364\/AO.38.006994","article-title":"Simultaneous amplitude-contrast and quantitative phase-contrast microscopy by numerical reconstruction of Fresnel off-axis holograms","volume":"38","author":"Cuche","year":"1999","journal-title":"Appl. Opt."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"3177","DOI":"10.1364\/JOSAA.23.003177","article-title":"Numerical parametric lens for shifting, magnification, and complete aberration compensation in digital holographic microscopy","volume":"23","author":"Colomb","year":"2006","journal-title":"J. Opt. Soc. Am. A"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"4070","DOI":"10.1364\/AO.39.004070","article-title":"Spatial filtering for zero-order and twin-image elimination in digital off-axis holography","volume":"39","author":"Cuche","year":"2000","journal-title":"Appl. Opt."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1456","DOI":"10.1109\/JPHOT.2012.2210199","article-title":"Automatic identification of malaria-infected RBC with digital holographic microscopy using correlation algorithms","volume":"4","author":"Anand","year":"2012","journal-title":"IEEE Photonics J."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"6900207","DOI":"10.1109\/JPHOT.2013.2278522","article-title":"Identification of Malaria-Infected Red Blood Cells Via Digital Shearing Interferometry and Statistical Inference","volume":"5","author":"Moon","year":"2013","journal-title":"IEEE Photonics J."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1111\/jmi.12331","article-title":"Diabetes screening by telecentric digital holographic microscopy","volume":"261","author":"Doblas","year":"2016","journal-title":"J. Microsc."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"13614","DOI":"10.1364\/OE.26.013614","article-title":"Sickle cell disease diagnosis based on spatio- temporal cell dynamics analysis using 3D printed shearing digital holographic microscopy","volume":"26","author":"Avidi","year":"2018","journal-title":"Opt. Express"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"7495","DOI":"10.1021\/acs.analchem.8b01076","article-title":"Label-Free Optical Marker for Red-Blood-Cell Phenotyping of Inherited Anemias","volume":"90","author":"Mugnano","year":"2018","journal-title":"Anal. Chem."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Isola, P., Zhu, J., Zhou, T., and Efros, A.A. (2017, January 21\u201326). Image-to-Image Translation with Conditional Adversarial Networks. Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, USA.","DOI":"10.1109\/CVPR.2017.632"},{"key":"ref_50","unstructured":"Kingma, D.P., and Ba, J.L. (2015, January 7\u20139). Adam: A method for stochastic optimization. Proceedings of the International Conference on Learning Representations, San Diego, CA, USA."},{"key":"ref_51","unstructured":"Leibe, B., Matas, J., Sebe, N., and Welling, M. (2016, January 8\u201316). Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks. Proceedings of the Computer Vision\u2014ECCV 2016, Amsterdam, The Netherlands."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Khalid, M., Baber, J., Kasi, M.K., Bakhtyar, M., Devi, V., and Sheikh, N. (2020, January 7\u20139). Empirical Evaluation of Activation Functions in Deep Convolution Neural Network for Facial Expression Recognition. Proceedings of the 2020 43rd International Conference on Telecommunications and Signal Processing (TSP), Milan, Italy.","DOI":"10.1109\/TSP49548.2020.9163446"},{"key":"ref_53","first-page":"12","article-title":"U-Net: Convolutional Networks for Biomedical Image Segmentation","volume":"9351","author":"Ronneberger","year":"2015","journal-title":"Lect. Notes Comput. Sci."},{"key":"ref_54","unstructured":"Brownlee, J. (2019). Generative Adversarial Networks with Python: Deep Learning Generative Models for Image Synthesis and Image Translation, Machine Learning Mastery."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1145\/3422622","article-title":"Generative Adversarial Networks","volume":"63","author":"Goodfellow","year":"2020","journal-title":"Commun. ACM"},{"key":"ref_56","unstructured":"(2021, November 20). cGAN QPI-DHM. Available online: https:\/\/oirl.github.io\/cGAN-Digital-Holographic-microscopy\/."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"713","DOI":"10.1029\/RS023i004p00713","article-title":"Satellite radar interferometry Two-dimensional phase unwrapping","volume":"23","author":"Goldstein","year":"1988","journal-title":"Radio Sci."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"1953","DOI":"10.1364\/JOSAA.21.001953","article-title":"Light scattering by multiple red blood cells","volume":"21","author":"He","year":"2004","journal-title":"J. Opt. Soc. Am. A"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"1416","DOI":"10.1364\/OL.41.001416","article-title":"Phase-shifting by means of an electronically tunable lens: Quantitative phase imaging of biological specimens with digital holographic microscopy","volume":"41","author":"Trujillo","year":"2016","journal-title":"Opt. Lett."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1117\/1.JBO.25.8.086501","article-title":"Advantages of Fresnel biprism-based digital holographic microscopy in quantitative phase imaging","volume":"25","author":"Skalli","year":"2020","journal-title":"J. Biomed. Opt."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/23\/8021\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:38:18Z","timestamp":1760168298000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/23\/8021"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,1]]},"references-count":60,"journal-issue":{"issue":"23","published-online":{"date-parts":[[2021,12]]}},"alternative-id":["s21238021"],"URL":"https:\/\/doi.org\/10.3390\/s21238021","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,12,1]]}}}