{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T19:52:55Z","timestamp":1771703575551,"version":"3.50.1"},"reference-count":34,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2023,6,8]],"date-time":"2023-06-08T00:00:00Z","timestamp":1686182400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"General Program of Natural Science Foundation of Sichuan Provincial","award":["2023NSFSC0636"],"award-info":[{"award-number":["2023NSFSC0636"]}]},{"name":"General Program of Natural Science Foundation of Sichuan Provincial","award":["82071940"],"award-info":[{"award-number":["82071940"]}]},{"name":"General Program of Natural Science Foundation of Sichuan Provincial","award":["2019YJ0055"],"award-info":[{"award-number":["2019YJ0055"]}]},{"name":"National Natural Science Foundation","award":["2023NSFSC0636"],"award-info":[{"award-number":["2023NSFSC0636"]}]},{"name":"National Natural Science Foundation","award":["82071940"],"award-info":[{"award-number":["82071940"]}]},{"name":"National Natural Science Foundation","award":["2019YJ0055"],"award-info":[{"award-number":["2019YJ0055"]}]},{"name":"the Applied Basic Research Program of Sichuan Province","award":["2023NSFSC0636"],"award-info":[{"award-number":["2023NSFSC0636"]}]},{"name":"the Applied Basic Research Program of Sichuan Province","award":["82071940"],"award-info":[{"award-number":["82071940"]}]},{"name":"the Applied Basic Research Program of Sichuan Province","award":["2019YJ0055"],"award-info":[{"award-number":["2019YJ0055"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Due to the heterogeneity of ultrasound (US) images and the indeterminate US texture of liver fibrosis (LF), automatic evaluation of LF based on US images is still challenging. Thus, this study aimed to propose a hierarchical Siamese network that combines the information from liver and spleen US images to improve the accuracy of LF grading. There were two stages in the proposed method. In stage one, a dual-channel Siamese network was trained to extract features from paired liver and spleen patches that were cropped from US images to avoid vascular interferences. Subsequently, the L1 distance was used to quantify the liver\u2013spleen differences (LSDs). In stage two, the pretrained weights from stage one were transferred into the Siamese feature extractor of the LF staging model, and a classifier was trained using the fusion of the liver and LSD features for LF staging. This study was retrospectively conducted on US images of 286 patients with histologically proven liver fibrosis stages. Our method achieved a precision and sensitivity of 93.92% and 91.65%, respectively, for cirrhosis (S4) diagnosis, which is about 8% higher than that of the baseline model. The accuracy of the advanced fibrosis (\u2265S3) diagnosis and the multi-staging of fibrosis (\u2264S2 vs. S3 vs. S4) both improved about 5% to reach 90.40% and 83.93%, respectively. This study proposed a novel method that combined hepatic and splenic US images and improved the accuracy of LF staging, which indicates the great potential of liver\u2013spleen texture comparison in noninvasive assessment of LF based on US images.<\/jats:p>","DOI":"10.3390\/s23125450","type":"journal-article","created":{"date-parts":[[2023,6,9]],"date-time":"2023-06-09T02:03:18Z","timestamp":1686276198000},"page":"5450","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["A Hierarchical Siamese Network for Noninvasive Staging of Liver Fibrosis Based on US Image Pairs of the Liver and Spleen"],"prefix":"10.3390","volume":"23","author":[{"given":"Xue","family":"Wang","sequence":"first","affiliation":[{"name":"College of Biomedical Engineering, Sichuan University, Chengdu 610065, China"}]},{"given":"Ling","family":"Song","sequence":"additional","affiliation":[{"name":"Department of Ultrasound, West China Hospital, Sichuan University, Chengdu 610065, China"}]},{"given":"Yan","family":"Zhuang","sequence":"additional","affiliation":[{"name":"College of Biomedical Engineering, Sichuan University, Chengdu 610065, China"}]},{"given":"Lin","family":"Han","sequence":"additional","affiliation":[{"name":"College of Biomedical Engineering, Sichuan University, Chengdu 610065, China"}]},{"given":"Ke","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Biomedical Engineering, Sichuan University, Chengdu 610065, China"}]},{"given":"Jiangli","family":"Lin","sequence":"additional","affiliation":[{"name":"College of Biomedical Engineering, Sichuan University, Chengdu 610065, China"}]},{"given":"Yan","family":"Luo","sequence":"additional","affiliation":[{"name":"Department of Ultrasound, West China Hospital, Sichuan University, Chengdu 610065, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,6,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1172\/JCI24282","article-title":"Liver fibrosis","volume":"115","author":"Bataller","year":"2005","journal-title":"J. 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