{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T05:25:15Z","timestamp":1761110715591,"version":"3.32.0"},"reference-count":62,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2024,10,4]],"date-time":"2024-10-04T00:00:00Z","timestamp":1728000000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J of Ultrasound Medicine"],"published-print":{"date-parts":[[2025,2]]},"abstract":"<jats:sec><jats:title>Objective<\/jats:title><jats:p>Fetal growth restriction (FGR) is a condition where fetuses fail to reach their genetic potential for growth, posing a significant health challenge for newborns. The aim of this research was to explore the efficacy of texture\u2010based analysis of neurosonographic images in identifying FGR in fetuses, which may provide a promising tool for early assessment of FGR.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>A retrospective analysis collected 100 intrauterine neurosonographic images from 50 FGR and 50 gestational age\u2010appropriate fetuses. Using MaZda software, approximately 300 texture features were extracted from occipital white matter (OWM) and cerebellum of intrauterine neurosonographic images, respectively. Then 10 optimal features were separately selected by 3 algorithms, including the Fisher coefficient method, the method of minimizing classification error probability and average correlation coefficients, and the mutual information coefficient method. Further, the 10 statistically most significant features were selected from these sets to form the mixed feature set. After nonlinear discriminant analysis was performed to reduce feature dimensionality, the artificial neural network (ANN) classifier was conducted, respectively.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>For OWM and cerebellum, a total of 11 and 14 statistically significant features were selected. When the mixed feature sets of OWM and cerebellum were applied to ANN classifier, classification accuracy were 90.00% (<jats:italic>\u03ba<\/jats:italic>\u2009=\u20090.800; <jats:italic>P<\/jats:italic>\u2009&lt;\u2009.001) and 93.00% (<jats:italic>\u03ba<\/jats:italic>\u2009=\u20090.860; <jats:italic>P<\/jats:italic>\u2009&lt;\u2009.001), and the receiver operating characteristic curve for identifying FGR showed an area under the curve of 0.82 and 0.87.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Texture analysis of fetal intrauterine neurosonographic images is a feasible and noninvasive strategy for evaluating FGR fetuses.<\/jats:p><\/jats:sec>","DOI":"10.1002\/jum.16594","type":"journal-article","created":{"date-parts":[[2024,10,4]],"date-time":"2024-10-04T12:43:37Z","timestamp":1728045817000},"page":"177-188","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Texture\u2010Based Classification of Fetal Growth Restriction From Intrauterine Neurosonographic Image"],"prefix":"10.1002","volume":"44","author":[{"given":"Zehao","family":"Chen","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology Dongguan University of Technology  Dongguan China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mengjie","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Medical Ultrasonics The Eighth Affiliated Hospital of Sun Yat\u2010sen University  Shenzhen China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shiying","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Medical Ultrasonics The Eighth Affiliated Hospital of Sun Yat\u2010sen University  Shenzhen China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhongming","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology Dongguan University of Technology  Dongguan China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yiheng","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology Dongguan University of Technology  Dongguan China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuhan","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology Dongguan University of Technology  Dongguan China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weiling","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology Dongguan University of Technology  Dongguan China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7625-6198","authenticated-orcid":false,"given":"Xiaowei","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology Dongguan University of Technology  Dongguan China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2024,10,4]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.3390\/metabo12090860"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.4137\/CMPed.S40070"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.pcl.2018.12.009"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1159\/000453576"},{"key":"e_1_2_8_6_1","unstructured":"ZeidanAM GillilandPR PatelA et al.PIPPI2021: an approach to automated diagnosis and texture analysis of the fetal liver & placenta in fetal growth restriction.arXiv preprint2022;2211.02639.https:\/\/doi.org\/10.48550\/arXiv.2211.02639."},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1002\/uog.20272"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.1002\/jum.16108"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.1159\/000357592"},{"key":"e_1_2_8_10_1","doi-asserted-by":"publisher","DOI":"10.1055\/s-0038-1660777"},{"key":"e_1_2_8_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.brainres.2011.01.032"},{"key":"e_1_2_8_12_1","doi-asserted-by":"publisher","DOI":"10.1111\/apa.15670"},{"key":"e_1_2_8_13_1","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.28408"},{"key":"e_1_2_8_14_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12194-019-00552-4"},{"key":"e_1_2_8_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2020.108838"},{"key":"e_1_2_8_16_1","doi-asserted-by":"publisher","DOI":"10.1002\/mp.13764"},{"key":"e_1_2_8_17_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-023-43055-4"},{"key":"e_1_2_8_18_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-020-06831-8"},{"key":"e_1_2_8_19_1","doi-asserted-by":"publisher","DOI":"10.3174\/ajnr.A6075"},{"key":"e_1_2_8_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.acra.2019.12.015"},{"key":"e_1_2_8_21_1","doi-asserted-by":"publisher","DOI":"10.1080\/14767058.2021.1887847"},{"key":"e_1_2_8_22_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajogmf.2021.100462"},{"issue":"1","key":"e_1_2_8_23_1","first-page":"1935","article-title":"Image characterization based fetal brain MRI localization and extraction","volume":"25","author":"Durgadevi P","year":"2021","journal-title":"Ann Rom Soc Cell Biol"},{"key":"e_1_2_8_24_1","doi-asserted-by":"publisher","DOI":"10.1259\/bjr.20210128"},{"key":"e_1_2_8_25_1","doi-asserted-by":"publisher","DOI":"10.12688\/f1000research.10401.1"},{"key":"e_1_2_8_26_1","doi-asserted-by":"publisher","DOI":"10.3233\/THC-191752"},{"key":"e_1_2_8_27_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11548-020-02182-3"},{"key":"e_1_2_8_28_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.pneurobio.2017.03.009"},{"key":"e_1_2_8_29_1","doi-asserted-by":"publisher","DOI":"10.1159\/000530492"},{"key":"e_1_2_8_30_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2023.1092357"},{"key":"e_1_2_8_31_1","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.28861"},{"key":"e_1_2_8_32_1","doi-asserted-by":"publisher","DOI":"10.5114\/pjr.2020.96950"},{"key":"e_1_2_8_33_1","doi-asserted-by":"publisher","DOI":"10.1097\/MPG.0b013e3181da213e"},{"key":"e_1_2_8_34_1","doi-asserted-by":"publisher","DOI":"10.1002\/uog.8831"},{"key":"e_1_2_8_35_1","doi-asserted-by":"publisher","DOI":"10.1002\/uog.22145"},{"key":"e_1_2_8_36_1","doi-asserted-by":"publisher","DOI":"10.1002\/uog.3909"},{"key":"e_1_2_8_37_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2008.08.005"},{"key":"e_1_2_8_38_1","first-page":"1","article-title":"Image texture feature extraction using GLCM approach","volume":"3","author":"Mohanaiah P","year":"2013","journal-title":"Int J Sci Res Publ"},{"key":"e_1_2_8_39_1","doi-asserted-by":"publisher","DOI":"10.1080\/09500340.2016.1154194"},{"key":"e_1_2_8_40_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-15-0853-0"},{"key":"e_1_2_8_41_1","doi-asserted-by":"publisher","DOI":"10.1109\/83.725367"},{"key":"e_1_2_8_42_1","doi-asserted-by":"publisher","DOI":"10.1109\/access.2018.2890743"},{"key":"e_1_2_8_43_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.1418724"},{"key":"e_1_2_8_44_1","article-title":"Nonlinear discriminant analysis using kernel functions","volume":"12","author":"Roth V","year":"1999","journal-title":"Adv Neural Inf Process Syst"},{"key":"e_1_2_8_45_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.nima.2012.09.006"},{"key":"e_1_2_8_46_1","doi-asserted-by":"publisher","DOI":"10.1109\/72.363467"},{"key":"e_1_2_8_47_1","doi-asserted-by":"publisher","DOI":"10.4324\/9780429287657"},{"key":"e_1_2_8_48_1","doi-asserted-by":"publisher","DOI":"10.1093\/humupd\/dmaa053"},{"key":"e_1_2_8_49_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.25006"},{"key":"e_1_2_8_50_1","doi-asserted-by":"publisher","DOI":"10.3389\/fphys.2018.01583"},{"key":"e_1_2_8_51_1","doi-asserted-by":"publisher","DOI":"10.3389\/frai.2021.622616"},{"key":"e_1_2_8_52_1","doi-asserted-by":"publisher","DOI":"10.1111\/jpc.15310"},{"key":"e_1_2_8_53_1","doi-asserted-by":"publisher","DOI":"10.1002\/jum.16001"},{"key":"e_1_2_8_54_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajog.2017.12.010"},{"key":"e_1_2_8_55_1","doi-asserted-by":"publisher","DOI":"10.3390\/children8090745"},{"key":"e_1_2_8_56_1","doi-asserted-by":"publisher","DOI":"10.3389\/fped.2020.00225"},{"key":"e_1_2_8_57_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpeds.2017.06.003"},{"key":"e_1_2_8_58_1","doi-asserted-by":"publisher","DOI":"10.1159\/000538123"},{"key":"e_1_2_8_59_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-016-4502-4"},{"key":"e_1_2_8_60_1","doi-asserted-by":"publisher","DOI":"10.1038\/pr.2017.37"},{"key":"e_1_2_8_61_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.placenta.2008.12.006"},{"key":"e_1_2_8_62_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2019.102014"},{"key":"e_1_2_8_63_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2022.119700"}],"container-title":["Journal of Ultrasound in Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/jum.16594","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,10]],"date-time":"2025-01-10T11:54:46Z","timestamp":1736510086000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/jum.16594"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,4]]},"references-count":62,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2025,2]]}},"alternative-id":["10.1002\/jum.16594"],"URL":"https:\/\/doi.org\/10.1002\/jum.16594","archive":["Portico"],"relation":{},"ISSN":["0278-4297","1550-9613"],"issn-type":[{"type":"print","value":"0278-4297"},{"type":"electronic","value":"1550-9613"}],"subject":[],"published":{"date-parts":[[2024,10,4]]},"assertion":[{"value":"2024-04-30","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-09-15","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-10-04","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}