{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T00:50:34Z","timestamp":1785891034536,"version":"3.56.0"},"reference-count":43,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100004731","name":"Zhejiang Province Natural Science Foundation","doi-asserted-by":"publisher","award":["LZ24E060002"],"award-info":[{"award-number":["LZ24E060002"]}],"id":[{"id":"10.13039\/501100004731","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100022955","name":"Fundamental Research Funds for the Provincial Universities of Zhejiang Province","doi-asserted-by":"publisher","award":["2024YW109"],"award-info":[{"award-number":["2024YW109"]}],"id":[{"id":"10.13039\/100022955","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52376079"],"award-info":[{"award-number":["52376079"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computers & Geosciences"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.cageo.2026.106230","type":"journal-article","created":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T20:22:53Z","timestamp":1782850973000},"page":"106230","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["RockAdaptive-FewSeg: A few-annotation segmentation framework for CT images of sandstone reservoir"],"prefix":"10.1016","volume":"215","author":[{"given":"Xin","family":"Mao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuxia","family":"Qiu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinqing","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingxiu","family":"Zhan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liang","family":"Lei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4349-5627","authenticated-orcid":false,"given":"Peng","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.cageo.2026.106230_bib1","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.cageo.2012.09.005","article-title":"Digital rock physics benchmarks\u2014Part I: imaging and segmentation","volume":"50","author":"Andr\u00e4","year":"2013","journal-title":"Comput. Geosci."},{"key":"10.1016\/j.cageo.2026.106230_bib2","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1007\/BF00238181","article-title":"Macroscopic modelling of transport phenomena in porous media. 1: the continuum approach","volume":"1","author":"Bachmat","year":"1986","journal-title":"Transport Porous Media"},{"key":"10.1016\/j.cageo.2026.106230_bib3","doi-asserted-by":"crossref","first-page":"336","DOI":"10.1016\/j.procir.2021.01.157","article-title":"Deep learning based porosity segmentation in X-ray CT measurements of polymer additive manufacturing parts","volume":"96","author":"Bellens","year":"2021","journal-title":"Proced. CIRP"},{"key":"10.1016\/j.cageo.2026.106230_bib4","doi-asserted-by":"crossref","DOI":"10.3389\/fmats.2021.761229","article-title":"A modular U-Net for automated segmentation of X-Ray tomography images in composite materials","volume":"8","author":"Bertoldo","year":"2021","journal-title":"Front. Mater."},{"key":"10.1016\/j.cageo.2026.106230_bib5","series-title":"Mathematical Morphology in Image Processing","first-page":"433","article-title":"The morphological approach to segmentation: the watershed transformation","author":"Beucher","year":"2018"},{"key":"10.1016\/j.cageo.2026.106230_bib6","doi-asserted-by":"crossref","DOI":"10.1016\/j.geoen.2024.212753","article-title":"Resolution enhancement and deblurring of porous media \u03bc-CT images based on super resolution generative adversarial network","volume":"236","author":"Cai","year":"2024","journal-title":"Geoenergy Sci. Eng."},{"key":"10.1016\/j.cageo.2026.106230_bib7","doi-asserted-by":"crossref","first-page":"3626","DOI":"10.1111\/mice.13300","article-title":"Deep learning\u2010based segmentation model for permeable concrete meso\u2010structures","volume":"39","author":"Chen","year":"2024","journal-title":"Comput. Aided Civ. Infrastruct. Eng."},{"key":"10.1016\/j.cageo.2026.106230_bib8","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/j.cageo.2019.05.003","article-title":"A novel method for extracting information on pores from cast thin-section images","volume":"130","author":"Dong","year":"2019","journal-title":"Comput. Geosci."},{"key":"10.1016\/j.cageo.2026.106230_bib9","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1016\/j.cemconcomp.2017.07.003","article-title":"Particle-based characterization of Ottawa sand: shape, size, mineralogy, and elastic moduli","volume":"83","author":"Erdo\u011fan","year":"2017","journal-title":"Cement Concr. Compos."},{"key":"10.1016\/j.cageo.2026.106230_bib10","doi-asserted-by":"crossref","first-page":"158","DOI":"10.46690\/ager.2025.02.07","article-title":"Integration of image recognition and expert system for real-time wellbore stability analysis","volume":"15","author":"Fan","year":"2025","journal-title":"Adv. Geo-Energy Res."},{"key":"10.1016\/j.cageo.2026.106230_bib11","series-title":"Brain Informatics and Health, Lecture Notes in Computer Science","first-page":"389","article-title":"A domain-expert centered process model for knowledge discovery in medical research: putting the expert-in-the-loop","author":"Girardi","year":"2015"},{"key":"10.1016\/j.cageo.2026.106230_bib12","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-020-78415-x","article-title":"Predicting porosity, permeability, and tortuosity of porous media from images by deep learning","volume":"10","author":"Graczyk","year":"2020","journal-title":"Sci. Rep."},{"key":"10.1016\/j.cageo.2026.106230_bib13","series-title":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE","first-page":"353","article-title":"RAU-Net: U-net model based on residual and attention for kidney and kidney tumor segmentation","author":"Guo","year":"2021"},{"key":"10.1016\/j.cageo.2026.106230_bib14","doi-asserted-by":"crossref","DOI":"10.1016\/j.compgeo.2024.106675","article-title":"Mapping distribution of fractures and minerals in rock samples using Res-VGG-UNet and threshold segmentation methods","volume":"175","author":"He","year":"2024","journal-title":"Comput. Geotech."},{"key":"10.1016\/j.cageo.2026.106230_bib15","series-title":"2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Presented at the 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), IEEE, Las Vegas, NV, USA","first-page":"770","article-title":"Deep residual learning for image recognition","author":"He","year":"2016"},{"key":"10.1016\/j.cageo.2026.106230_bib16","doi-asserted-by":"crossref","DOI":"10.1016\/j.compgeo.2023.105887","article-title":"Property evaluation by numerical modelling based on voxelized images \u2013 accuracy versus resolution","volume":"165","author":"Jiang","year":"2024","journal-title":"Comput. Geotech."},{"key":"10.1016\/j.cageo.2026.106230_bib17","series-title":"Advances in Visual Computing. ISVC 2023. Lecture Notes in Computer Science","article-title":"A few-shot attention recurrent residual u-net for crack segmentation","author":"Katsamenis","year":"2023"},{"key":"10.1016\/j.cageo.2026.106230_bib18","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1145\/3065386","article-title":"ImageNet classification with deep convolutional neural networks","volume":"60","author":"Krizhevsky","year":"2017","journal-title":"Commun. ACM"},{"key":"10.1016\/j.cageo.2026.106230_bib19","doi-asserted-by":"crossref","DOI":"10.1088\/1742-6596\/2467\/1\/012016","article-title":"Pore extraction method of rock thin section based on attention U-Net","volume":"2467","author":"Li","year":"2023","journal-title":"J. Phys., Conf. Ser."},{"key":"10.1016\/j.cageo.2026.106230_bib20","article-title":"Segmentation of backscattered electron images of cement-based materials using lightweight U-Net with attention mechanism (LWAU-Net)","volume":"77","author":"Li","year":"2023","journal-title":"J. Build. Eng."},{"key":"10.1016\/j.cageo.2026.106230_bib22","doi-asserted-by":"crossref","DOI":"10.1016\/j.compgeo.2023.105412","article-title":"Fault-seg-net: a method for seismic fault segmentation based on multi-scale feature fusion with imbalanced classification","volume":"158","author":"Li","year":"2023","journal-title":"Comput. Geotech."},{"key":"10.1016\/j.cageo.2026.106230_bib21","doi-asserted-by":"crossref","first-page":"5","DOI":"10.46690\/ager.2023.04.02","article-title":"Advances in the application of deep learning methods to digital rock technology","volume":"8","author":"Li","year":"2023","journal-title":"Adv. Geo-Energy Res."},{"key":"10.1016\/j.cageo.2026.106230_bib23","doi-asserted-by":"crossref","first-page":"1333","DOI":"10.1016\/j.ijheatmasstransfer.2019.04.110","article-title":"Effect of pore characteristic on the percolation threshold and diffusivity of porous media comprising overlapping concave-shaped pores","volume":"138","author":"Lin","year":"2019","journal-title":"Int. J. Heat Mass Tran."},{"key":"10.1016\/j.cageo.2026.106230_bib24","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.media.2017.07.005","article-title":"A survey on deep learning in medical image analysis","volume":"42","author":"Litjens","year":"2017","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.cageo.2026.106230_bib25","doi-asserted-by":"crossref","DOI":"10.1016\/j.cageo.2024.105745","article-title":"Shale sample permeability estimation using fractal parameters computed from TransUnet-based SEM image segmentation","volume":"194","author":"Liu","year":"2025","journal-title":"Comput. Geosci."},{"key":"10.1016\/j.cageo.2026.106230_bib26","doi-asserted-by":"crossref","first-page":"3352","DOI":"10.3390\/app14083352","article-title":"A novel method combining U-Net with LSTM for three-dimensional soil pore segmentation based on computed tomography images","volume":"14","author":"Liu","year":"2024","journal-title":"Appl. Sci."},{"key":"10.1016\/j.cageo.2026.106230_bib27","doi-asserted-by":"crossref","DOI":"10.1007\/s42835-022-01118-y","article-title":"Research on image segmentation algorithm and performance of power insulator based on adaptive region growing","author":"Liu","year":"2022","journal-title":"J. Electr. Eng. Technol."},{"key":"10.1016\/j.cageo.2026.106230_bib28","doi-asserted-by":"crossref","DOI":"10.1016\/j.compgeo.2021.104468","article-title":"Predicting the permeability of consolidated silty clay via digital soil reconstruction","volume":"140","author":"Liu","year":"2021","journal-title":"Comput. Geotech."},{"key":"10.1016\/j.cageo.2026.106230_bib29","doi-asserted-by":"crossref","first-page":"5206","DOI":"10.1109\/TIP.2020.2980170","article-title":"An adaptive and robust edge detection method based on edge proportion statistics","volume":"29","author":"Liu","year":"2020","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.cageo.2026.106230_bib30","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1007\/s11242-025-02190-4","article-title":"Improving numerical fluid flow simulation by ring artifact removal in Micro-CT images of porous media using attention autoencoder\u2013decoders","volume":"152","author":"Mahdaviara","year":"2025","journal-title":"Transport Porous Media"},{"key":"10.1016\/j.cageo.2026.106230_bib31","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1016\/1047-3203(90)90014-M","article-title":"Morphological segmentation","volume":"1","author":"Meyer","year":"1990","journal-title":"J. Vis. Commun. Image Represent."},{"key":"10.1016\/j.cageo.2026.106230_bib32","doi-asserted-by":"crossref","DOI":"10.1038\/sdata.2019.4","article-title":"An X-ray computed micro-tomography dataset for oil removal from carbonate porous media","volume":"6","author":"Pak","year":"2019","journal-title":"Sci. Data"},{"key":"10.1016\/j.cageo.2026.106230_bib33","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1186\/s40494-022-00723-4","article-title":"High-resolution micro-CT with 3D image analysis for porosity characterization of historic bricks","volume":"10","author":"Reedy","year":"2022","journal-title":"Heritage Sci."},{"key":"10.1016\/j.cageo.2026.106230_bib34","series-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2015, Lecture Notes in Computer Science","first-page":"234","article-title":"U-Net: Convolutional networks for biomedical image segmentation","author":"Ronneberger","year":"2015"},{"key":"10.1016\/j.cageo.2026.106230_bib35","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1186\/s12880-015-0068-x","article-title":"Metrics for evaluating 3D medical image segmentation: analysis, selection, and tool","volume":"15","author":"Taha","year":"2015","journal-title":"BMC Med. Imag."},{"key":"10.1016\/j.cageo.2026.106230_bib37","series-title":"Proceedings of the 31st International Conference on Neural Information Processing Systems, NIPS\u201917","first-page":"6000","article-title":"Attention is all you need","author":"Vaswani","year":"2017"},{"key":"10.1016\/j.cageo.2026.106230_bib36","article-title":"Microcomputed tomography\u2013based characterization of advanced materials: a review","volume":"8","author":"V\u00e1s\u00e1rhelyi","year":"2020","journal-title":"Mater Today Adv."},{"key":"10.1016\/j.cageo.2026.106230_bib38","doi-asserted-by":"crossref","first-page":"129","DOI":"10.46690\/ager.2025.02.05","article-title":"Intelligent identification of coal fractures using an improvedU-shaped network","volume":"15","author":"Wang","year":"2025","journal-title":"Adv. Geo-Energy Res."},{"key":"10.1016\/j.cageo.2026.106230_bib39","doi-asserted-by":"crossref","first-page":"25","DOI":"10.46690\/ager.2021.01.04","article-title":"Formation damage mechanism of a sandstone reservoir based on micro-computed tomography","volume":"5","author":"Wang","year":"2021","journal-title":"Adv. Geo-Energy Res."},{"key":"10.1016\/j.cageo.2026.106230_bib40","doi-asserted-by":"crossref","DOI":"10.1016\/j.engeos.2023.100185","article-title":"Extraction of fractures in shale CT images using improved U-Net","volume":"5","author":"Wu","year":"2024","journal-title":"Energy Geosci."},{"key":"10.1016\/j.cageo.2026.106230_bib41","doi-asserted-by":"crossref","first-page":"71","DOI":"10.46690\/ager.2023.08.01","article-title":"Recent advances on fluid flow in porous media using digital core analysis technology","volume":"9","author":"Yang","year":"2023","journal-title":"Adv. Geo-Energy Res."},{"key":"10.1016\/j.cageo.2026.106230_bib42","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1016\/j.compgeo.2015.11.025","article-title":"Segmentation of contacting soil particles in images by modified watershed analysis","volume":"73","author":"Zheng","year":"2016","journal-title":"Comput. Geotech."},{"key":"10.1016\/j.cageo.2026.106230_bib43","series-title":"2007 Third International IEEE Conference on Signal-Image Technologies and Internet-based System","article-title":"An image segmentation algorithm in image processing based on threshold segmentation","author":"Zhu","year":"2007"}],"container-title":["Computers & Geosciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0098300426001275?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0098300426001275?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T00:09:39Z","timestamp":1785888579000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0098300426001275"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":43,"alternative-id":["S0098300426001275"],"URL":"https:\/\/doi.org\/10.1016\/j.cageo.2026.106230","relation":{},"ISSN":["0098-3004"],"issn-type":[{"value":"0098-3004","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"RockAdaptive-FewSeg: A few-annotation segmentation framework for CT images of sandstone reservoir","name":"articletitle","label":"Article Title"},{"value":"Computers & Geosciences","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.cageo.2026.106230","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"106230"}}