{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T02:07:13Z","timestamp":1781057233337,"version":"3.54.1"},"reference-count":36,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2023,3,15]],"date-time":"2023-03-15T00:00:00Z","timestamp":1678838400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Changsha Municipal &amp; Natural Science Foundation","award":["kq2014160"],"award-info":[{"award-number":["kq2014160"]}]},{"name":"Changsha Municipal &amp; Natural Science Foundation","award":["61703441"],"award-info":[{"award-number":["61703441"]}]},{"name":"Changsha Municipal &amp; Natural Science Foundation","award":["2020JJ4948"],"award-info":[{"award-number":["2020JJ4948"]}]},{"name":"Changsha Municipal &amp; Natural Science Foundation","award":["19A511"],"award-info":[{"award-number":["19A511"]}]},{"name":"National Natural Science Foundation in China","award":["kq2014160"],"award-info":[{"award-number":["kq2014160"]}]},{"name":"National Natural Science Foundation in China","award":["61703441"],"award-info":[{"award-number":["61703441"]}]},{"name":"National Natural Science Foundation in China","award":["2020JJ4948"],"award-info":[{"award-number":["2020JJ4948"]}]},{"name":"National Natural Science Foundation in China","award":["19A511"],"award-info":[{"award-number":["19A511"]}]},{"name":"National Natural Science Foundation of Hunan Province","award":["kq2014160"],"award-info":[{"award-number":["kq2014160"]}]},{"name":"National Natural Science Foundation of Hunan Province","award":["61703441"],"award-info":[{"award-number":["61703441"]}]},{"name":"National Natural Science Foundation of Hunan Province","award":["2020JJ4948"],"award-info":[{"award-number":["2020JJ4948"]}]},{"name":"National Natural Science Foundation of Hunan Province","award":["19A511"],"award-info":[{"award-number":["19A511"]}]},{"name":"Department of Education Hunan Province","award":["kq2014160"],"award-info":[{"award-number":["kq2014160"]}]},{"name":"Department of Education Hunan Province","award":["61703441"],"award-info":[{"award-number":["61703441"]}]},{"name":"Department of Education Hunan Province","award":["2020JJ4948"],"award-info":[{"award-number":["2020JJ4948"]}]},{"name":"Department of Education Hunan Province","award":["19A511"],"award-info":[{"award-number":["19A511"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>The automatic recognition of CT (Computed Tomography) images of liver cancer is important for the diagnosis and treatment of early liver cancer. However, there are problems such as single model structure and loss of pooling layer information when using a traditional convolutional neural network to recognize CT images of liver cancer. Therefore, this paper proposes an efficient method for liver CT image recognition based on the capsule network (CapsNet). Firstly, the liver CT images are preprocessed, and in the process of image denoising, the traditional non-local mean (NLM) denoising algorithm is optimized with a superpixel segmentation algorithm to better protect the information of image edges. After that, CapsNet was used for image recognition for liver CT images. The experimental results show that the average recognition rate of liver CT images reaches 92.9% when CapsNet is used, which is 5.3% higher than the traditional CNN model, indicating that CapsNet has better recognition accuracy for liver CT images.<\/jats:p>","DOI":"10.3390\/info14030183","type":"journal-article","created":{"date-parts":[[2023,3,15]],"date-time":"2023-03-15T04:39:45Z","timestamp":1678855185000},"page":"183","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Liver CT Image Recognition Method Based on Capsule Network"],"prefix":"10.3390","volume":"14","author":[{"given":"Qifan","family":"Wang","sequence":"first","affiliation":[{"name":"School of Computer & Information Engineering, Central South University of Forest & Technology, Changsha 410000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aibin","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Computer & Information Engineering, Central South University of Forest & Technology, Changsha 410000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3733-631X","authenticated-orcid":false,"given":"Yongfei","family":"Xue","sequence":"additional","affiliation":[{"name":"School of Computer & Information Engineering, Central South University of Forest & Technology, Changsha 410000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,3,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"394","DOI":"10.3322\/caac.21492","article-title":"Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries","volume":"68","author":"Bray","year":"2018","journal-title":"CA A Cancer J. 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