{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T16:18:57Z","timestamp":1779293937895,"version":"3.51.4"},"reference-count":70,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2021,12,10]],"date-time":"2021-12-10T00:00:00Z","timestamp":1639094400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51905393 12102311"],"award-info":[{"award-number":["51905393 12102311"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Bioeng. Biotechnol."],"abstract":"<jats:p>Retinal vessels are the only deep micro vessels that can be observed in human body, the accurate identification of which has great significance on the diagnosis of hypertension, diabetes and other diseases. To this end, a retinal vessel segmentation algorithm based on residual convolution neural network is proposed according to the characteristics of the retinal vessels on fundus images. Improved residual attention module and deep supervision module are utilized, in which the low-level and high-level feature graphs are joined to construct the encoder-decoder network structure, and atrous convolution is introduced to the pyramid pooling. The experiments result on the fundus image data set DRIVE and STARE show that this algorithm can obtain complete retinal vessel segmentation as well as connected vessel stems and terminals. The average accuracy on DRIVE and STARE reaches 95.90 and 96.88%, and the average specificity is 98.85 and 97.85%, which shows superior performance compared to other methods. This algorithm is verified feasible and effective for retinal vessel segmentation of fundus images and has the ability to detect more capillaries.<\/jats:p>","DOI":"10.3389\/fbioe.2021.786425","type":"journal-article","created":{"date-parts":[[2021,12,10]],"date-time":"2021-12-10T05:58:55Z","timestamp":1639115935000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":18,"title":["Retinal Vessel Segmentation Algorithm Based on Residual Convolution Neural Network"],"prefix":"10.3389","volume":"9","author":[{"given":"Shuang","family":"Xu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiqiang","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weiyi","family":"Cao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Feng","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bo","family":"Tao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2021,12,10]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"568","DOI":"10.1016\/j.amc.2018.07.057","article-title":"Blood Vessel Segmentation in Retinal Fundus Images Using Gabor Filters, Fractional Derivatives, and Expectation Maximization","volume":"339","author":"Aguirre-Ramos","year":"2018","journal-title":"Appl. Mathematics Comput."},{"key":"B2","doi-asserted-by":"publisher","first-page":"797","DOI":"10.1007\/s11760-020-01798-x","article-title":"Performance Analysis of Automated Lesion Detection of Diabetic Retinopathy Using Morphological Operation","volume":"15","author":"Alaguselvi","year":"2021","journal-title":"Signal. Image Video Process. Volume"},{"key":"B3","doi-asserted-by":"publisher","first-page":"5082","DOI":"10.1109\/TNNLS.2020.3026784","article-title":"Revisiting Internal Covariate Shift for Batch Normalization","volume":"32","author":"Awais","year":"2021","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"B4","doi-asserted-by":"publisher","first-page":"51","DOI":"10.13382\/j.jemi.2017.01.008","article-title":"Retinal Vessel Segmentation Method Based on Matched Filtering and Automatic Threshold","volume":"1","author":"Cao","year":"2017","journal-title":"J. Electron. Meas. Instrumentation"},{"key":"B5","doi-asserted-by":"publisher","first-page":"193","DOI":"10.3390\/e22020193","article-title":"Deep Residual Learning for Nonlinear Regression","volume":"22","author":"Chen","year":"2020","journal-title":"Entropy"},{"key":"B6","doi-asserted-by":"publisher","first-page":"834","DOI":"10.1109\/tpami.2017.2699184","article-title":"DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs","volume":"40","author":"Chen","year":"2018","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"B7","doi-asserted-by":"publisher","first-page":"1341","DOI":"10.3390\/math9121341","article-title":"Analysis of User Needs on Downloading Behavior of English Vocabulary APPs Based on Data Mining for Online Comments","volume":"9","author":"Chen","year":"","journal-title":"Mathematics"},{"key":"B8","doi-asserted-by":"publisher","first-page":"176","DOI":"10.3390\/healthcare9020176","article-title":"Combining Public Opinion Dissemination with Polarization Process Considering Individual Heterogeneity","volume":"9","author":"Chen","year":"","journal-title":"Healthcare"},{"key":"B9","doi-asserted-by":"publisher","first-page":"106","DOI":"10.3390\/axioms10020106","article-title":"Monitoring and Recognizing enterprise Public Opinion from High-Risk Users Based on User Portrait and Random forest Algorithm","volume":"10","author":"Chen","year":"","journal-title":"Axioms"},{"key":"B10","doi-asserted-by":"publisher","first-page":"2","DOI":"10.4103\/0301-4738.178155","article-title":"Diabetic Retinopathy: Battling the Global Epidemic","volume":"64","author":"Das","year":"2016","journal-title":"Indian J. Ophthalmol."},{"key":"B11","doi-asserted-by":"publisher","first-page":"158","DOI":"10.1504\/IJBIC.2020.111267","article-title":"An Effective Improved Co-evolution Ant colony Optimisation Algorithm with Multi-Strategies and its Application","volume":"16","author":"Deng","year":"2020","journal-title":"Ijbic"},{"key":"B12","doi-asserted-by":"publisher","first-page":"1471","DOI":"10.1007\/s11831-020-09425-1","article-title":"Histogram Equalization Variants as Optimization Problems: A Review","volume":"28","author":"Dhal","year":"2020","journal-title":"Arch. Computat Methods Eng."},{"key":"B13","doi-asserted-by":"publisher","first-page":"41885","DOI":"10.1109\/ACCESS.2019.2906344","article-title":"A New Hybrid Algorithm for Retinal Vessels Segmentation on Fundus Images","volume":"7","author":"Dharmawan","year":"","journal-title":"IEEE Access"},{"key":"B14","doi-asserted-by":"publisher","first-page":"1511","DOI":"10.1109\/LSP.2019.2938631","article-title":"Design of Optimal Adaptive Filters for Two-Dimensional Filamentary Structures Segmentation","volume":"26","author":"Dharmawan","year":"","journal-title":"IEEE Signal. Process. Lett."},{"key":"B15","doi-asserted-by":"publisher","first-page":"188","DOI":"10.14004\/j.cnki.ckt.2019.1884","article-title":"Retinal Blood Vessel Segmentation Based on Matched Filtering and Morphological Processing","volume":"15","author":"Fan","year":"2019","journal-title":"Computer Knowledge Technology"},{"key":"B16","doi-asserted-by":"publisher","first-page":"4696","DOI":"10.1109\/TIP.2020.2975919","article-title":"Residual Learning for Salient Object Detection","volume":"29","author":"Feng","year":"2020","journal-title":"IEEE Trans. Image Process."},{"key":"B17","doi-asserted-by":"publisher","first-page":"96","DOI":"10.1016\/j.artmed.2019.02.004","article-title":"Joint Segmentation and Classification of Retinal Arteries\/veins from Fundus Images","volume":"94","author":"Girard","year":"2019","journal-title":"Artif. Intelligence Med."},{"key":"B18","doi-asserted-by":"publisher","first-page":"309","DOI":"10.1016\/j.jcjo.2018.04.019","article-title":"Deep Learning in Ophthalmology: a Review","volume":"53","author":"Grewal","year":"2018","journal-title":"Can. J. Ophthalmol."},{"key":"B19","doi-asserted-by":"publisher","first-page":"586","DOI":"10.1016\/j.measurement.2018.05.003","article-title":"A Retinal Vessel Detection Approach Using Convolution Neural Network with Reinforcement Sample Learning Strategy","volume":"125","author":"Guo","year":"2018","journal-title":"Measurement"},{"key":"B20","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1136\/emermed-2017-206735","article-title":"What Is an ROC Curve?","volume":"34","author":"Hoo","year":"2017","journal-title":"Emerg. Med. J."},{"key":"B21","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1109\/42.845178","article-title":"Locating Blood Vessels in Retinal Images by Piecewise Threshold Probing of a Matched Filter Response","volume":"19","author":"Hoover","year":"2000","journal-title":"IEEE Trans. Med. Imaging"},{"key":"B22","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1007\/s11892-016-0813-8","article-title":"Clinical Components of Telemedicine Programs for Diabetic Retinopathy","volume":"16","author":"Horton","year":"2016","journal-title":"Curr. Diab Rep."},{"key":"B23","doi-asserted-by":"publisher","first-page":"2011","DOI":"10.1109\/TPAMI.2019.2913372","article-title":"Squeeze-and-Excitation Networks","volume":"42","author":"Hu","year":"2020","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"B24","doi-asserted-by":"publisher","first-page":"45","DOI":"10.3390\/e22010045","article-title":"(Multiscale) Cross-Entropy Methods: A Review","volume":"22","author":"Jamin","year":"2020","journal-title":"Entropy"},{"key":"B25","doi-asserted-by":"publisher","first-page":"1397","DOI":"10.1093\/ije\/dyz274","article-title":"Reflection on Modern Methods: Revisiting the Area under the ROC Curve","volume":"49","author":"Janssens","year":"2020","journal-title":"Int. J. Epidemiol."},{"key":"B26","doi-asserted-by":"publisher","first-page":"10809","DOI":"10.1007\/s12652-020-02843-w","article-title":"Manipulator Grabbing Position Detection with Information Fusion of Color Image and Depth Image Using Deep Learning","volume":"12","author":"Jiang","year":"","journal-title":"J. Ambient Intell. Hum. Comput"},{"key":"B27","doi-asserted-by":"publisher","first-page":"94","DOI":"10.1016\/j.future.2021.04.019","article-title":"Semantic Segmentation for Multiscale Target Based on Object Recognition Using the Improved Faster-RCNN Model","volume":"123","author":"Jiang","year":"","journal-title":"Future Generation Computer Syst."},{"key":"B28","doi-asserted-by":"publisher","first-page":"1585","DOI":"10.1007\/s11042-015-3147-7","article-title":"Improved Local Histogram Equalization with Gradient-Based Weighting Process for Edge Preservation","volume":"76","author":"Lai","year":"2015","journal-title":"Multimed Tools Appl."},{"key":"B29","doi-asserted-by":"publisher","first-page":"11533","DOI":"10.1109\/ACCESS.2019.2891749","article-title":"Human Lesion Detection Method Based on Image Information and Brain Signal","volume":"7","author":"Li","year":"","journal-title":"IEEE Access"},{"key":"B30","doi-asserted-by":"publisher","first-page":"347","DOI":"10.1093\/biomet\/asz081","article-title":"The Essential Histogram","volume":"107","author":"Li","year":"","journal-title":"Biometrika"},{"key":"B31","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1504\/IJBIC.2021.114101","article-title":"Learning the Number of Filters in Convolutional Neural Networks","volume":"17","author":"Li","year":"","journal-title":"Ijbic"},{"key":"B32","doi-asserted-by":"publisher","first-page":"116430","DOI":"10.1016\/j.image.2021.116430","article-title":"Recursive Residual Atrous Spatial Pyramid Pooling Network for Single Image Deraining","volume":"99","author":"Li","year":"","journal-title":"Signal. Processing: Image Commun."},{"key":"B33","doi-asserted-by":"publisher","first-page":"19572","DOI":"10.1109\/ACCESS.2019.2897692","article-title":"Large-Margin Regularized Softmax Cross-Entropy Loss","volume":"7","author":"Li","year":"","journal-title":"IEEE Access"},{"key":"B34","doi-asserted-by":"publisher","first-page":"2083","DOI":"10.11772\/j.issn.1001-9081.2017123045","article-title":"Retinal Vessel Segmentation Algorithm Based on Hybrid Phase Feature","volume":"38","author":"Li","year":"2018","journal-title":"J. Computer Appl."},{"key":"B35","first-page":"601","article-title":"Retinal Vessel Segmentation Based on Deep forest","volume":"29","author":"Li","year":"","journal-title":"J. Yunnan Nationalities Univ. (Natural Sci. Edition)"},{"key":"B36","doi-asserted-by":"publisher","first-page":"107622","DOI":"10.1016\/j.patcog.2020.107622","article-title":"Cascaded Hierarchical Atrous Spatial Pyramid Pooling Module for Semantic Segmentation","volume":"110","author":"Lian","year":"2021","journal-title":"Pattern Recognition"},{"key":"B37","doi-asserted-by":"publisher","first-page":"7171","DOI":"10.1007\/s11227-020-03551-0","article-title":"Construction and Verification of Color Fundus Image Retinal Vessels Segmentation Algorithm under BP Neural Network","volume":"77","author":"Liu","year":"2021","journal-title":"J. Supercomput"},{"key":"B38","doi-asserted-by":"publisher","first-page":"1288","DOI":"10.3969\/j.issn.1672-8513.2020.06.012","article-title":"Segmentation of Retinal Blood Vessels Combining Attention and Conditional Generative Adversarial Network","volume":"42","author":"Lu","year":"2021","journal-title":"J. Chin. Computer Syst."},{"key":"B39","doi-asserted-by":"publisher","first-page":"519","DOI":"10.3969\/j.issn.0258-8021.2016.05.002","article-title":"A Universal Vessel Segmentation Method Based on Multi-Scale Filtering and Statistical Mixture Model","volume":"35","author":"Lu","year":"2016","journal-title":"Chin. J. Biomed. Eng."},{"key":"B40","doi-asserted-by":"publisher","first-page":"146","DOI":"10.1109\/TMI.2010.2064333","article-title":"A New Supervised Method for Blood Vessel Segmentation in Retinal Images by Using Gray-Level and Moment Invariants-Based Features","volume":"30","author":"Mar\u00edn","year":"2011","journal-title":"IEEE Trans. Med. Imaging"},{"key":"B41","doi-asserted-by":"publisher","first-page":"433","DOI":"10.1093\/biostatistics\/kxy010","article-title":"The ROC Curve for Regularly Measured Longitudinal Biomarkers","volume":"20","author":"Michael","year":"2019","journal-title":"Biostatistics"},{"key":"B42","doi-asserted-by":"publisher","first-page":"696","DOI":"10.1007\/s00357-019-09345-1","article-title":"ROC and AUC with a Binary Predictor: a Potentially Misleading Metric","volume":"37","author":"Muschelli","year":"2020","journal-title":"J. Classif"},{"key":"B43","doi-asserted-by":"publisher","first-page":"865","DOI":"10.1016\/j.bbe.2020.03.001","article-title":"Retinal Vasculature Segmentation and Measurement Framework for Color Fundus and SLO Images","volume":"40","author":"Pachade","year":"2020","journal-title":"Biocybernetics Biomed. Eng."},{"key":"B44","doi-asserted-by":"publisher","first-page":"373","DOI":"10.1007\/s11045-018-0561-9","article-title":"Morphological Operations with Iterative Rotation of Structuring Elements for Segmentation of Retinal Vessel Structures","volume":"30","author":"Pal","year":"2019","journal-title":"Multidim Syst. Sign Process."},{"key":"B45","doi-asserted-by":"publisher","first-page":"1357","DOI":"10.1109\/TMI.2007.898551","article-title":"Retinal Blood Vessel Segmentation Using Line Operators and Support Vector Classification","volume":"26","author":"Ricci","year":"2007","journal-title":"IEEE Trans. Med. Imaging"},{"key":"B46","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1016\/j.bspc.2017.03.014","article-title":"Segmentation of Optic Disc and Blood Vessels in Retinal Images Using Wavelets, Mathematical Morphology and Hessian-Based Multi-Scale Filtering","volume":"36","author":"Rodrigues","year":"2017","journal-title":"Biomed. Signal Process. Control."},{"key":"B47","doi-asserted-by":"publisher","first-page":"34839","DOI":"10.1007\/s11042-019-08111-0","article-title":"Blood Vessel Segmentation of Retinal Image Using Clifford Matched Filter and Clifford Convolution","volume":"78","author":"Roy","year":"2019","journal-title":"Multimed Tools Appl."},{"key":"B48","doi-asserted-by":"publisher","first-page":"921","DOI":"10.3969\/j.issn.1003-3106.2021.09.012","article-title":"Synthetic Aperture Radar Lmage Enhancement Based on Adaptive Histogram Equalization","volume":"51","author":"Shi","year":"2021","journal-title":"Radio Eng."},{"key":"B49","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1016\/j.cmpb.2016.03.001","article-title":"Retinal Blood Vessels Segmentation by Using Gumbel Probability Distribution Function Based Matched Filter","volume":"129","author":"Singh","year":"2016","journal-title":"Computer Methods Programs Biomed."},{"key":"B50","doi-asserted-by":"publisher","first-page":"71696","DOI":"10.1109\/ACCESS.2019.2920616","article-title":"Deep Learning Models for Retinal Blood Vessels Segmentation: A Review","volume":"7","author":"Soomro","year":"2019","journal-title":"IEEE Access"},{"key":"B51","doi-asserted-by":"publisher","first-page":"501","DOI":"10.1109\/tmi.2004.825627","article-title":"Ridge-based Vessel Segmentation in Color Images of the Retina","volume":"23","author":"Staal","year":"2004","journal-title":"IEEE Trans. Med. Imaging"},{"key":"B52","doi-asserted-by":"publisher","first-page":"2092","DOI":"10.1080\/02664763.2020.1784853","article-title":"Equal-bin-width Histogram versus Equal-Bin-Count Histogram","volume":"48","author":"Sulewski","year":"2020","journal-title":"J. Appl. Stat."},{"key":"B53","doi-asserted-by":"publisher","first-page":"4132","DOI":"10.1007\/s11227-018-2255-3","article-title":"Gear Reducer Optimal Design Based on Computer Multimedia Simulation","volume":"76","author":"Sun","year":"","journal-title":"J. Supercomput"},{"key":"B54","doi-asserted-by":"publisher","first-page":"3662","DOI":"10.1049\/iet-ipr.2020.0148","article-title":"Gesture Recognition Algorithm Based on Multi\u2010scale Feature Fusion in RGB\u2010D Images","volume":"14","author":"Sun","year":"","journal-title":"IET image process"},{"key":"B55","doi-asserted-by":"publisher","first-page":"1149","DOI":"10.1016\/j.aej.2020.01.015","article-title":"Intelligent Human Computer Interaction Based on Non Redundant EMG Signal","volume":"59","author":"Sun","year":"","journal-title":"Alexandria Eng. J."},{"key":"B56","doi-asserted-by":"publisher","first-page":"3870","DOI":"10.1007\/s11227-020-03422-8","article-title":"Construction and Verification of Retinal Vessel Segmentation Algorithm for Color Fundus Image under BP Neural Network Model","volume":"77","author":"Tang","year":"2021","journal-title":"J. Supercomput"},{"key":"B57","doi-asserted-by":"publisher","first-page":"5900","DOI":"10.3390\/s21175900","article-title":"A Time Sequence Images Matching Method Based on the Siamese Network","volume":"21","author":"Tao","year":"","journal-title":"Sensors"},{"key":"B58","doi-asserted-by":"publisher","first-page":"e6481","DOI":"10.1002\/CPE.6481","article-title":"3D Reconstruction Based on Photoelastic Fringes","author":"Tao","year":"","journal-title":"Concurrency Computat Pract. Exper"},{"key":"B59","doi-asserted-by":"publisher","first-page":"82","DOI":"10.3788\/aos202141.0410001","article-title":"Retinal Blood Vessel Segmentation Based on Multi-Scale Wavelet Transform Fusion","volume":"41","author":"Tian","year":"2021","journal-title":"Acta Optica Sinica"},{"key":"B60","doi-asserted-by":"publisher","first-page":"802","DOI":"10.1001\/jamaophthalmol.2016.1284","article-title":"Visual Impairment and Blindness in Adults in the United States","volume":"134","author":"Varma","year":"2016","journal-title":"JAMA Ophthalmol."},{"key":"B61","doi-asserted-by":"publisher","first-page":"177","DOI":"10.1016\/j.neucom.2019.05.008","article-title":"Rademacher Dropout: An Adaptive Dropout for Deep Neural Network via Optimizing Generalization gap","volume":"357","author":"Wang","year":"2019","journal-title":"Neurocomputing"},{"key":"B62","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1016\/j.jvcir.2018.05.020","article-title":"Blind Forensics of Image Gamma Transformation and its Application in Splicing Detection","volume":"55","author":"Wang","year":"2018","journal-title":"J. Vis. Commun. Image Representation"},{"key":"B63","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2021\/5563698","article-title":"Weak-Light Image Enhancement Method Based on Adaptive Local Gamma Transform and Color Compensation","volume":"2021","author":"Wang","year":"2021","journal-title":"J. Sensors"},{"key":"B64","doi-asserted-by":"publisher","first-page":"483","DOI":"10.2147\/PRBM.S303239","article-title":"Understanding the Relationship between Tourists' Consumption Behavior and Their Consumption Substitution Willingness under Unusual Environment","volume":"14","author":"Xiang","year":"2021","journal-title":"Psychol. Res. Behav. Manag."},{"key":"B65","doi-asserted-by":"publisher","first-page":"101060","DOI":"10.1016\/j.elerap.2021.101060","article-title":"A Novel POI Recommendation Method Based on Trust Relationship and Spatial-Temporal Factors","volume":"48","author":"Xu","year":"","journal-title":"Electron. Commerce Res. Appl."},{"key":"B66","doi-asserted-by":"publisher","first-page":"260","DOI":"10.1109\/tcsvt.2020.2975671","article-title":"Cross-View Gait Recognition Using Pairwise Spatial Transformer Networks","volume":"31","author":"Xu","year":"","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"B67","doi-asserted-by":"publisher","first-page":"1427","DOI":"10.1109\/JBHI.2018.2872813","article-title":"A Three-Stage Deep Learning Model for Accurate Retinal Vessel Segmentation","volume":"23","author":"Yan","year":"2019","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"B68","doi-asserted-by":"publisher","first-page":"779353","DOI":"10.3389\/fbioe.2021.779353","article-title":"Dynamic Gesture Recognition Using Surface EMG Signals Based on Multi-Stream Residual Network","volume":"9","author":"Yang","year":"2021","journal-title":"Front. Bioeng. Biotechnol."},{"key":"B69","volume-title":"The Retinal Identification Based on Principal Component Analysis","author":"Zhang","year":"2020"},{"key":"B70","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1504\/IJBIC.2020.105899","article-title":"Improved Density Peaks Clustering Based on Firefly Algorithm","volume":"15","author":"Zhao","year":"2020","journal-title":"Int. J. Bio-Inspired Comput."}],"container-title":["Frontiers in Bioengineering and Biotechnology"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fbioe.2021.786425\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,12,10]],"date-time":"2021-12-10T05:59:04Z","timestamp":1639115944000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fbioe.2021.786425\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,10]]},"references-count":70,"alternative-id":["10.3389\/fbioe.2021.786425"],"URL":"https:\/\/doi.org\/10.3389\/fbioe.2021.786425","relation":{},"ISSN":["2296-4185"],"issn-type":[{"value":"2296-4185","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,12,10]]},"article-number":"786425"}}