{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,13]],"date-time":"2026-06-13T01:57:48Z","timestamp":1781315868662,"version":"3.54.1"},"reference-count":44,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2020,9,28]],"date-time":"2020-09-28T00:00:00Z","timestamp":1601251200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2020,9,28]],"date-time":"2020-09-28T00:00:00Z","timestamp":1601251200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/100000070","name":"U.S. Department of Health & Human Services | NIH | National Institute of Biomedical Imaging and Bioengineering","doi-asserted-by":"publisher","award":["EB022899"],"award-info":[{"award-number":["EB022899"]}],"id":[{"id":"10.13039\/100000070","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000070","name":"U.S. Department of Health & Human Services | NIH | National Institute of Biomedical Imaging and Bioengineering","doi-asserted-by":"publisher","award":["EB022899"],"award-info":[{"award-number":["EB022899"]}],"id":[{"id":"10.13039\/100000070","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000070","name":"U.S. Department of Health & Human Services | NIH | National Institute of Biomedical Imaging and Bioengineering","doi-asserted-by":"publisher","award":["EB022899"],"award-info":[{"award-number":["EB022899"]}],"id":[{"id":"10.13039\/100000070","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000070","name":"U.S. Department of Health & Human Services | NIH | National Institute of Biomedical Imaging and Bioengineering","doi-asserted-by":"publisher","award":["EB022899"],"award-info":[{"award-number":["EB022899"]}],"id":[{"id":"10.13039\/100000070","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000070","name":"U.S. Department of Health & Human Services | NIH | National Institute of Biomedical Imaging and Bioengineering","doi-asserted-by":"publisher","award":["EB022899"],"award-info":[{"award-number":["EB022899"]}],"id":[{"id":"10.13039\/100000070","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000025","name":"U.S. Department of Health & Human Services | NIH | National Institute of Mental Health","doi-asserted-by":"publisher","award":["MH114824"],"award-info":[{"award-number":["MH114824"]}],"id":[{"id":"10.13039\/100000025","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000025","name":"U.S. Department of Health & Human Services | NIH | National Institute of Mental Health","doi-asserted-by":"publisher","award":["MH114821"],"award-info":[{"award-number":["MH114821"]}],"id":[{"id":"10.13039\/100000025","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000025","name":"U.S. Department of Health & Human Services | NIH | National Institute of Mental Health","doi-asserted-by":"publisher","award":["MH114821"],"award-info":[{"award-number":["MH114821"]}],"id":[{"id":"10.13039\/100000025","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000025","name":"U.S. Department of Health & Human Services | NIH | National Institute of Mental Health","doi-asserted-by":"publisher","award":["MH114821"],"award-info":[{"award-number":["MH114821"]}],"id":[{"id":"10.13039\/100000025","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000025","name":"U.S. Department of Health & Human Services | NIH | National Institute of Mental Health","doi-asserted-by":"publisher","award":["MH114821"],"award-info":[{"award-number":["MH114821"]}],"id":[{"id":"10.13039\/100000025","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000025","name":"U.S. Department of Health & Human Services | NIH | National Institute of Mental Health","doi-asserted-by":"publisher","award":["MH114821"],"award-info":[{"award-number":["MH114821"]}],"id":[{"id":"10.13039\/100000025","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000025","name":"U.S. Department of Health & Human Services | NIH | National Institute of Mental Health","doi-asserted-by":"publisher","award":["MH114821"],"award-info":[{"award-number":["MH114821"]}],"id":[{"id":"10.13039\/100000025","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000065","name":"U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke","doi-asserted-by":"publisher","award":["NS107466"],"award-info":[{"award-number":["NS107466"]}],"id":[{"id":"10.13039\/100000065","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100008460","name":"U.S. Department of Health & Human Services | NIH | National Center for Complementary and Integrative Health","doi-asserted-by":"publisher","award":["AT010414"],"award-info":[{"award-number":["AT010414"]}],"id":[{"id":"10.13039\/100008460","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Crick-Clay Professorship, Mathers Charitable Foundation, H N Mahabala Chair"},{"name":"H N Mahabala Chair"},{"DOI":"10.13039\/100000143","name":"NSF | Directorate for Computer & Information Science & Engineering | Division of Computing and Communication Foundations","doi-asserted-by":"publisher","award":["CCF-1740761"],"award-info":[{"award-number":["CCF-1740761"]}],"id":[{"id":"10.13039\/100000143","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000145","name":"NSF | Directorate for Computer & Information Science & Engineering | Division of Information and Intelligent Systems","doi-asserted-by":"publisher","award":["RI-1815697"],"award-info":[{"award-number":["RI-1815697"]}],"id":[{"id":"10.13039\/100000145","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000121","name":"NSF | Directorate for Mathematical & Physical Sciences | Division of Mathematical Sciences","doi-asserted-by":"publisher","award":["DMS-1547457"],"award-info":[{"award-number":["DMS-1547457"]}],"id":[{"id":"10.13039\/100000121","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Nat Mach Intell"],"DOI":"10.1038\/s42256-020-0227-9","type":"journal-article","created":{"date-parts":[[2020,9,28]],"date-time":"2020-09-28T12:05:06Z","timestamp":1601294706000},"page":"585-594","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":36,"title":["Semantic segmentation of microscopic neuroanatomical data by combining topological priors with encoder\u2013decoder deep networks"],"prefix":"10.1038","volume":"2","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2325-1489","authenticated-orcid":false,"given":"Samik","family":"Banerjee","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lucas","family":"Magee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3888-9250","authenticated-orcid":false,"given":"Dingkang","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xu","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bing-Xing","family":"Huo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8925-723X","authenticated-orcid":false,"given":"Jaikishan","family":"Jayakumar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6105-4219","authenticated-orcid":false,"given":"Katherine","family":"Matho","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Meng-Kuan","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Keerthi","family":"Ram","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohanasankar","family":"Sivaprakasam","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0592-028X","authenticated-orcid":false,"given":"Josh","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7950-4348","authenticated-orcid":false,"given":"Yusu","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8818-6804","authenticated-orcid":false,"given":"Partha P.","family":"Mitra","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,9,28]]},"reference":[{"key":"227_CR1","doi-asserted-by":"publisher","first-page":"e1000334","DOI":"10.1371\/journal.pcbi.1000334","volume":"5","author":"JW Bohland","year":"2009","unstructured":"Bohland, J. W. et al. A proposal for a coordinated effort for the determination of brainwide neuroanatomical connectivity in model organisms at a mesoscopic scale. PLoS Comput. Biol. 5, e1000334 (2009).","journal-title":"PLoS Comput. Biol."},{"key":"227_CR2","doi-asserted-by":"publisher","first-page":"331","DOI":"10.1038\/nmeth1036","volume":"4","author":"H-U Dodt","year":"2007","unstructured":"Dodt, H.-U. et al. Ultramicroscopy: three-dimensional visualization of neuronal networks in the whole mouse brain. Nat. Methods 4, 331\u2013336 (2007).","journal-title":"Nat. Methods"},{"key":"227_CR3","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1038\/nmeth.1854","volume":"9","author":"T Ragan","year":"2012","unstructured":"Ragan, T. et al. Serial two-photon tomography for automated ex vivo mouse brain imaging. Nat. Methods 9, 255 (2012).","journal-title":"Nat. Methods"},{"key":"227_CR4","doi-asserted-by":"publisher","first-page":"207","DOI":"10.1038\/nature13186","volume":"508","author":"SW Oh","year":"2014","unstructured":"Oh, S. W. et al. A mesoscale connectome of the mouse brain. Nature 508, 207\u2013214 (2014).","journal-title":"Nature"},{"key":"227_CR5","doi-asserted-by":"publisher","first-page":"e0102363","DOI":"10.1371\/journal.pone.0102363","volume":"10","author":"V Pinskiy","year":"2015","unstructured":"Pinskiy, V. et al. High-throughput method of whole-brain sectioning, using the tape-transfer technique. PLoS ONE 10, e0102363 (2015).","journal-title":"PLoS ONE"},{"key":"227_CR6","doi-asserted-by":"publisher","first-page":"e40042","DOI":"10.7554\/eLife.40042","volume":"8","author":"MK Lin","year":"2019","unstructured":"Lin, M. K. et al. A high-throughput neurohistological pipeline for brain-wide mesoscale connectivity mapping of the common marmoset. eLife 8, e40042 (2019).","journal-title":"eLife"},{"key":"227_CR7","doi-asserted-by":"publisher","first-page":"49","DOI":"10.3389\/fnins.2012.00049","volume":"6","author":"M Halavi","year":"2012","unstructured":"Halavi, M., Hamilton, K. A., Parekh, R. & Ascoli, G. Digital reconstructions of neuronal morphology: three decades of research trends. Front. Neurosci. 6, 49 (2012).","journal-title":"Front. Neurosci."},{"key":"227_CR8","doi-asserted-by":"publisher","first-page":"162","DOI":"10.1016\/j.conb.2011.11.010","volume":"22","author":"M Helmstaedter","year":"2012","unstructured":"Helmstaedter, M. & Mitra, P. P. Computational methods and challenges for large-scale circuit mapping. Curr. Opin. Neurobiol. 22, 162\u2013169 (2012).","journal-title":"Curr. Opin. Neurobiol."},{"key":"227_CR9","doi-asserted-by":"publisher","first-page":"259","DOI":"10.1007\/s12021-015-9270-9","volume":"13","author":"H Peng","year":"2015","unstructured":"Peng, H., Meijering, E. & Ascoli, G. A. From DIADEM to BigNeuron. Neuroinform. 13, 259\u2013260 (2015).","journal-title":"Neuroinform."},{"key":"227_CR10","doi-asserted-by":"publisher","first-page":"39","DOI":"10.3389\/fninf.2014.00039","volume":"8","author":"N Rey-Villamizar","year":"2014","unstructured":"Rey-Villamizar, N. et al. Large-scale automated image analysis for computational profiling of brain tissue surrounding implanted neuroprosthetic devices using Python. Front. Neuroinform. 8, 39 (2014).","journal-title":"Front. Neuroinform."},{"key":"227_CR11","doi-asserted-by":"publisher","first-page":"252","DOI":"10.1016\/j.neuron.2015.06.036","volume":"87","author":"H Peng","year":"2015","unstructured":"Peng, H. et al. BigNeuron: large-scale 3D neuron reconstruction from optical microscopy images. Neuron 87, 252\u2013256 (2015).","journal-title":"Neuron"},{"key":"227_CR12","doi-asserted-by":"publisher","first-page":"110","DOI":"10.1192\/bjp.172.2.110","volume":"172","author":"SM Lawrie","year":"1998","unstructured":"Lawrie, S. M. & Abukmeil, S. S. Brain abnormality in schizophrenia: a systematic and quantitative review of volumetric magnetic resonance imaging studies. Br. J. Psychiatry 172, 110\u2013120 (1998).","journal-title":"Br. J. Psychiatry"},{"key":"227_CR13","unstructured":"Taylor, R. H., Lavealle, S., Burdea, G. C. & Mosges, R. Computer-integrated Surgery: Technology and Clinical Applications (MIT Press, 1995)."},{"key":"227_CR14","first-page":"401","volume":"22","author":"AP Zijdenbos","year":"1994","unstructured":"Zijdenbos, A. P. & Dawant, B. M. Brain segmentation and white matter lesion detection in MR images. Crit. Rev. Biomed. Eng. 22, 401\u2013465 (1994).","journal-title":"Crit. Rev. Biomed. Eng."},{"key":"227_CR15","doi-asserted-by":"publisher","first-page":"1161","DOI":"10.1142\/S0218001497000548","volume":"11","author":"AJ Worth","year":"1997","unstructured":"Worth, A. J., Makris, N., Caviness, V. S.Jr & Kennedy, D. N. Neuroanatomical segmentation in MRI: technological objectives. Int. J. Pattern Recognit. Artif. Intell. 11, 1161\u20131187 (1997).","journal-title":"Int. J. Pattern Recognit. Artif. Intell."},{"key":"227_CR16","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/S0167-8140(96)01866-X","volume":"42","author":"VS Khoo","year":"1997","unstructured":"Khoo, V. S. et al. Magnetic resonance imaging (MRI): considerations and applications in radiotherapy treatment planning. Radiother. Oncol. 42, 1\u201315 (1997).","journal-title":"Radiother. Oncol."},{"key":"227_CR17","doi-asserted-by":"publisher","first-page":"1367","DOI":"10.1142\/S0218001497000639","volume":"11","author":"WEL Grimson","year":"1997","unstructured":"Grimson, W. E. L. et al. Utilizing segmented mri data in image-guided surgery. Int. J. Pattern Recognit. Artif. Intell. 11, 1367\u20131397 (1997).","journal-title":"Int. J. Pattern Recognit. Artif. Intell."},{"key":"227_CR18","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","volume":"521","author":"Y LeCun","year":"2015","unstructured":"LeCun, Y., Bengio, Y. & Hinton, G. Deep learning. Nature 521, 436\u2013444 (2015).","journal-title":"Nature"},{"key":"227_CR19","doi-asserted-by":"publisher","first-page":"2278","DOI":"10.1109\/5.726791","volume":"86","author":"Y LeCun","year":"1998","unstructured":"LeCun, Y., Bottou, L., Bengio, Y. & Haffner, P. Gradient-based learning applied to document recognition. Proc. IEEE 86, 2278\u20132324 (1998).","journal-title":"Proc. IEEE"},{"key":"227_CR20","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1007\/BF00344251","volume":"36","author":"K Fukushima","year":"1980","unstructured":"Fukushima, K. Neocognitron: a self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position. Biol. Cybern. 36, 193\u2013202 (1980).","journal-title":"Biol. Cybern."},{"key":"227_CR21","doi-asserted-by":"publisher","unstructured":"Pahariya, G. et al. High precision automated detection of labeled nuclei in gigapixel resolution image data of mouse brain. Preprint at BioRxiv https:\/\/doi.org\/10.1101\/252247 (2019).","DOI":"10.1101\/252247"},{"key":"227_CR22","doi-asserted-by":"crossref","unstructured":"Ramesh, N., Yoo, J.-H. & Sethi, I. Thresholding based on histogram approximation. In IEEE Proc.\u2014Vision, Image and Signal Processing Vol. 142, 271\u2013279 (IEEE, 1995).","DOI":"10.1049\/ip-vis:19952007"},{"key":"227_CR23","doi-asserted-by":"publisher","first-page":"119","DOI":"10.4103\/0971-6203.42763","volume":"33","author":"N Sharma","year":"2008","unstructured":"Sharma, N. et al. Segmentation and classification of medical images using texture-primitive features: application of BAM-type artificial neural network. J. Med. Phys. 33, 119\u2013126 (2008).","journal-title":"J. Med. Phys."},{"key":"227_CR24","doi-asserted-by":"crossref","unstructured":"Boykov, Y. Y. & Jolly, M.-P. Interactive graph cuts for optimal boundary and region segmentation of objects in nd images. In Proc. Eighth IEEE International Conference on Computer Vision, ICCV 2001 Vol. 1, 105\u2013112 (IEEE, 2001).","DOI":"10.1109\/ICCV.2001.937505"},{"key":"227_CR25","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1016\/j.media.2017.07.005","volume":"42","author":"G Litjens","year":"2017","unstructured":"Litjens, G. et al. A survey on deep learning in medical image analysis. Med. Image Anal. 42, 60\u201388 (2017).","journal-title":"Med. Image Anal."},{"key":"227_CR26","unstructured":"Krizhevsky, A., Sutskever, I. & Hinton, G. E. ImageNet classification with deep convolutional neural networks. In Advances in Neural Information Processing Systems 25 (NIPS 2012) 1097\u20131105 (NIPS, 2012)."},{"key":"227_CR27","doi-asserted-by":"crossref","unstructured":"He, K., Gkioxari, G., Doll\u00e1r, P. & Girshick, R. Mask R-CNN. In Proc. IEEE International Conference on Computer Vision 2961\u20132969 (IEEE, 2017).","DOI":"10.1109\/ICCV.2017.322"},{"key":"227_CR28","doi-asserted-by":"crossref","unstructured":"Redmon, J., Divvala, S., Girshick, R. & Farhadi, A. You only look once: unified, real-time object detection. In Proc. IEEE Conference on Computer Vision and Pattern Recognition 779\u2013788 (IEEE, 2016).","DOI":"10.1109\/CVPR.2016.91"},{"key":"227_CR29","doi-asserted-by":"publisher","first-page":"652","DOI":"10.1109\/TPAMI.2016.2587640","volume":"39","author":"O Vinyals","year":"2016","unstructured":"Vinyals, O., Toshev, A., Bengio, S. & Erhan, D. Show and tell: lessons learned from the 2015 MSCOCO image captioning challenge. IEEE Trans. Pattern Anal. Mach. Intell. 39, 652\u2013663 (2016).","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"227_CR30","unstructured":"Sabour, S., Frosst, N. & Hinton, G. E. Dynamic routing between capsules. In Advances in Neural Information Processing Systems 30 (NIPS 2017) 3856\u20133866 (NIPS, 2017)."},{"key":"227_CR31","doi-asserted-by":"publisher","first-page":"2481","DOI":"10.1109\/TPAMI.2016.2644615","volume":"39","author":"V Badrinarayanan","year":"2017","unstructured":"Badrinarayanan, V., Kendall, A. & Cipolla, R. Segnet: a deep convolutional encoder\u2013decoder architecture for image segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 39, 2481\u20132495 (2017).","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"227_CR32","doi-asserted-by":"crossref","unstructured":"Ronneberger, O., Fischer, P. & Brox, T. U-net: convolutional networks for biomedical image segmentation. In Int. Conference on Medical Image Computing and Computer-assisted Intervention 234\u2013241 (Springer, 2015).","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"227_CR33","doi-asserted-by":"crossref","unstructured":"Buslaev, A., Seferbekov, S. S., Iglovikov, V. & Shvets, A. Fully convolutional network for automatic road extraction from satellite imagery. In 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) 197\u20131973 (IEEE, 2018).","DOI":"10.1109\/CVPRW.2018.00035"},{"key":"227_CR34","unstructured":"Belkin, M., Hsu, D. J. & Mitra, P. Overfitting or perfect fitting? Risk bounds for classification and regression rules that interpolate. Advances in Neural Information Processing Systems 31 (NIPS 2018) 2300\u20132311 (NIPS, 2018)."},{"key":"227_CR35","doi-asserted-by":"crossref","unstructured":"Ci\u00e7ek, \u00d6., Abdulkadir, A., Lienkamp, S. S., Brox, T. & Ronneberger, O. 3D U-Net: learning dense volumetric segmentation from sparse annotation. In International Conference on Medical Image Computing and Computer-assisted Intervention 424\u2013432 (Springer, 2016).","DOI":"10.1007\/978-3-319-46723-8_49"},{"key":"227_CR36","doi-asserted-by":"crossref","unstructured":"Milletari, F., Navab, N. & Ahmadi, S.-A. V-Net: fully convolutional neural networks for volumetric medical image segmentation. In 2016 Fourth International Conference on 3D Vision (3DV) 565\u2013571 (IEEE, 2016).","DOI":"10.1109\/3DV.2016.79"},{"key":"227_CR37","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-019-0192-5","volume":"6","author":"JM Johnson","year":"2019","unstructured":"Johnson, J. M. & Khoshgoftaar, T. M. Survey on deep learning with class imbalance. J. Big Data 6, 27 (2019).","journal-title":"J. Big Data"},{"key":"227_CR38","doi-asserted-by":"publisher","first-page":"654","DOI":"10.1109\/TPAMI.2014.2346172","volume":"37","author":"O Delgado-Friedrichs","year":"2014","unstructured":"Delgado-Friedrichs, O., Robins, V. & Sheppard, A. Skeletonization and partitioning of digital images using discrete Morse theory. IEEE Trans. Pattern Anal. Mach. Intell. 37, 654\u2013666 (2014).","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"227_CR39","doi-asserted-by":"publisher","first-page":"1619","DOI":"10.1109\/TVCG.2008.110","volume":"14","author":"A Gyulassy","year":"2008","unstructured":"Gyulassy, A., Bremer, P.-T., Hamann, B. & Pascucci, V. A practical approach to Morse\u2013Smale complex computation: scalability and generality. IEEE Trans. Vis. Comput. Graph. 14, 1619\u20131626 (2008).","journal-title":"IEEE Trans. Vis. Comput. Graph."},{"key":"227_CR40","doi-asserted-by":"publisher","first-page":"1646","DOI":"10.1109\/TPAMI.2011.95","volume":"33","author":"V Robins","year":"2011","unstructured":"Robins, V., Wood, P. J. & Sheppard, A. P. Theory and algorithms for constructing discrete Morse complexes from grayscale digital images. IEEE Trans. Pattern Anal. Mach. Intell. 33, 1646\u20131658 (2011).","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"227_CR41","doi-asserted-by":"crossref","unstructured":"Dey, T. K., Wang, J. & Wang, Y. Road network reconstruction from satellite images with machine learning supported by topological methods. In Proc. 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems 520\u2013523 (ACM, 2019).","DOI":"10.1145\/3347146.3359348"},{"key":"227_CR42","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1090\/conm\/453\/08802","volume":"453","author":"H Edelsbrunner","year":"2008","unstructured":"Edelsbrunner, H. & Harer, J. Persistent homology\u2014a survey. Contemp. Math. 453, 257\u2013282 (2008).","journal-title":"Contemp. Math."},{"key":"227_CR43","unstructured":"Forman, R. A user\u2019s guide to discrete Morse theory. S\u00e9m. Lothar. Combin. 48, B48c (2002)."},{"key":"227_CR44","doi-asserted-by":"publisher","first-page":"1655","DOI":"10.1111\/j.1365-2966.2007.12685.x","volume":"383","author":"T Sousbie","year":"2008","unstructured":"Sousbie, T., Pichon, C., Colombi, S., Novikov, D. & Pogosyan, D. The 3D skeleton: tracing the filamentary structure of the Universe. Mon. Not. R. Astron. Soc. 383, 1655\u20131670 (2008).","journal-title":"Mon. Not. R. Astron. Soc."}],"container-title":["Nature Machine Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s42256-020-0227-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s42256-020-0227-9","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s42256-020-0227-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,14]],"date-time":"2024-08-14T20:34:39Z","timestamp":1723667679000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s42256-020-0227-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,9,28]]},"references-count":44,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2020,10]]}},"alternative-id":["227"],"URL":"https:\/\/doi.org\/10.1038\/s42256-020-0227-9","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/2020.02.18.955237","asserted-by":"object"}]},"ISSN":["2522-5839"],"issn-type":[{"value":"2522-5839","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,9,28]]},"assertion":[{"value":"5 March 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 August 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 September 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}]}}