{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T15:41:27Z","timestamp":1788450087327,"version":"build-2803163510"},"reference-count":51,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2021,10,14]],"date-time":"2021-10-14T00:00:00Z","timestamp":1634169600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62006156"],"award-info":[{"award-number":["62006156"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["91959108"],"award-info":[{"award-number":["91959108"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Science and Technology Project of Guangdong Province","award":["2018A050501014"],"award-info":[{"award-number":["2018A050501014"]}]},{"name":"Science Foundation of Shenzhen","award":["JSGG20180508152022006"],"award-info":[{"award-number":["JSGG20180508152022006"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,1,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>3D neuron segmentation is a key step for the neuron digital reconstruction, which is essential for exploring brain circuits and understanding brain functions. However, the fine line-shaped nerve fibers of neuron could spread in a large region, which brings great computational cost to the neuron segmentation. Meanwhile, the strong noises and disconnected nerve fibers bring great challenges to the task.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>In this article, we propose a 3D wavelet and deep learning-based 3D neuron segmentation method. The neuronal image is first partitioned into neuronal cubes to simplify the segmentation task. Then, we design 3D WaveUNet, the first 3D wavelet integrated encoder\u2013decoder network, to segment the nerve fibers in the cubes; the wavelets could assist the deep networks in suppressing data noises and connecting the broken fibers. We also produce a Neuronal Cube Dataset (NeuCuDa) using the biggest available annotated neuronal image dataset, BigNeuron, to train 3D WaveUNet. Finally, the nerve fibers segmented in cubes are assembled to generate the complete neuron, which is digitally reconstructed using an available automatic tracing algorithm. The experimental results show that our neuron segmentation method could completely extract the target neuron in noisy neuronal images. The integrated 3D wavelets can efficiently improve the performance of 3D neuron segmentation and reconstruction.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availabilityand implementation<\/jats:title>\n                    <jats:p>The data and codes for this work are available at https:\/\/github.com\/LiQiufu\/3D-WaveUNet.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Supplementary information<\/jats:title>\n                    <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btab716","type":"journal-article","created":{"date-parts":[[2021,10,12]],"date-time":"2021-10-12T09:19:07Z","timestamp":1634030347000},"page":"809-817","source":"Crossref","is-referenced-by-count":22,"title":["Neuron segmentation using 3D wavelet integrated encoder\u2013decoder network"],"prefix":"10.1093","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8120-6531","authenticated-orcid":false,"given":"Qiufu","family":"Li","sequence":"first","affiliation":[{"name":"Computer Vision Institute, College of Computer Science and Software Engineering, Shenzhen University , Shenzhen 518060, China"},{"name":"AI Research Center for Medical Image Analysis and Diagnosis, Shenzhen University , Shenzhen 518060, China"},{"name":"Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen University , Shenzhen 518060, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Linlin","family":"Shen","sequence":"additional","affiliation":[{"name":"Computer Vision Institute, College of Computer Science and Software Engineering, Shenzhen University , Shenzhen 518060, China"},{"name":"AI Research Center for Medical Image Analysis and Diagnosis, Shenzhen University , Shenzhen 518060, China"},{"name":"Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen University , Shenzhen 518060, China"},{"name":"Marshall Laboratory of Biomedical Engineering, Shenzhen University, Shenzhen 518060, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2021,10,14]]},"reference":[{"key":"2023020108500495000_btab716-B1","doi-asserted-by":"crossref","first-page":"738","DOI":"10.1109\/TVCG.2015.2467441","article-title":"Neuroblocks\u2013visual tracking of segmentation and proofreading for large connectomics projects","volume":"22","author":"Ai-Awami","year":"2016","journal-title":"IEEE Trans. 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