{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T15:40:38Z","timestamp":1773675638554,"version":"3.50.1"},"reference-count":33,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2025,9,22]],"date-time":"2025-09-22T00:00:00Z","timestamp":1758499200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,9,22]],"date-time":"2025-09-22T00:00:00Z","timestamp":1758499200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Evolving Systems"],"published-print":{"date-parts":[[2025,12]]},"DOI":"10.1007\/s12530-025-09737-2","type":"journal-article","created":{"date-parts":[[2025,9,22]],"date-time":"2025-09-22T06:02:54Z","timestamp":1758520974000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Pixelated disparity network for hepatocellular carcinoma recognition from ultrasound images"],"prefix":"10.1007","volume":"16","author":[{"given":"S.","family":"Usha","sequence":"first","affiliation":[]},{"given":"Saroj","family":"Bala","sequence":"additional","affiliation":[]},{"given":"M. D.","family":"Saranya","sequence":"additional","affiliation":[]},{"given":"S.","family":"Suganyadevi","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,9,22]]},"reference":[{"issue":"1","key":"9737_CR1","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1186\/s43055-023-00982-6","volume":"54","author":"AH Abduljabbar","year":"2023","unstructured":"Abduljabbar AH (2023) Diagnostic accuracy of ultrasound and alpha-fetoprotein measurement for hepatocellular carcinoma surveillance: a retrospective comparative study. Egypt J Radiol Nucl Med 54(1):31","journal-title":"Egypt J Radiol Nucl Med"},{"issue":"5","key":"9737_CR2","doi-asserted-by":"publisher","first-page":"1318","DOI":"10.1016\/j.ultrasmedbio.2023.01.021","volume":"49","author":"KG Brown","year":"2023","unstructured":"Brown KG, Li J, Margolis R, Trinh B, Eisenbrey JR, Hoyt K (2023) Assessment of transarterial chemoembolization using super-resolution ultrasound imaging and a rat model of hepatocellular carcinoma. Ultrasound Med Biol 49(5):1318\u20131326","journal-title":"Ultrasound Med Biol"},{"issue":"4","key":"9737_CR3","doi-asserted-by":"publisher","first-page":"625","DOI":"10.3390\/diagnostics13040625","volume":"13","author":"G Candita","year":"2023","unstructured":"Candita G, Rossi S, Cwiklinska K, Fanni SC, Cioni D, Lencioni R, Neri E (2023) Imaging diagnosis of hepatocellular carcinoma: a state-of-the-art review. Diagnostics 13(4):625","journal-title":"Diagnostics"},{"issue":"7","key":"9737_CR4","doi-asserted-by":"publisher","first-page":"1337","DOI":"10.3390\/diagnostics13071337","volume":"13","author":"K Chen","year":"2023","unstructured":"Chen K, Xu Y, Dong Y, Han H, Mao F, Wang H, Song X, Luo R, Wang WP (2023) Contrast-enhanced imaging features and clinicopathological investigation of steatohepatitic hepatocellular carcinoma. Diagnostics 13(7):1337","journal-title":"Diagnostics"},{"issue":"3","key":"9737_CR5","doi-asserted-by":"publisher","first-page":"553","DOI":"10.1016\/j.ajpath.2021.11.009","volume":"192","author":"S Diao","year":"2022","unstructured":"Diao S, Tian Y, Hu W, Hou J, Lambo R, Zhang Z, Xie Y, Nie X, Zhang Fa, Racoceanu D, Qin W (2022) Weakly supervised framework for cancer region detection of hepatocellular carcinoma in whole-slide pathologic images based on multiscale attention convolutional neural network. Am J Pathol 192(3):553\u2013563","journal-title":"Am J Pathol"},{"issue":"9","key":"9737_CR6","doi-asserted-by":"publisher","first-page":"1797","DOI":"10.1016\/j.ultrasmedbio.2022.05.005","volume":"48","author":"Y Dong","year":"2022","unstructured":"Dong Y, Wang WP, Lee WJ, Meloni MF, Clevert DA, Chammas MC, Tannapfel A, Forgione A, Piscaglia F, Dietrich CF (2022) Contrast-enhanced ultrasound features of histopathologically proven hepatocellular carcinoma in the non-cirrhotic liver: a multicenter study. Ultrasound Med Biol 48(9):1797\u20131805","journal-title":"Ultrasound Med Biol"},{"issue":"10","key":"9737_CR7","doi-asserted-by":"publisher","first-page":"e723","DOI":"10.1016\/j.crad.2022.06.003","volume":"77","author":"YY Duan","year":"2022","unstructured":"Duan YY, Qin J, Qiu WQ, Li SY, Li C, Liu AS, Chen X, Zhang CX (2022) Performance of a generative adversarial network using ultrasound images to stage liver fibrosis and predict cirrhosis based on a deep-learning radiomics nomogram. Clin Radiol 77(10):e723\u2013e731","journal-title":"Clin Radiol"},{"key":"9737_CR8","doi-asserted-by":"publisher","DOI":"10.32604\/cmc.2023.037728","author":"MK Elbashir","year":"2023","unstructured":"Elbashir MK, Mahmoud A, Mostafa AM, Hamouda E, Alruily M, Alotaibi SM, Mohamed Mostafa A, Shabana H, Ezz M (2023) A transfer learning approach based on ultrasound images for liver cancer detection. Comput Mater Contin. https:\/\/doi.org\/10.32604\/cmc.2023.037728","journal-title":"Comput Mater Contin"},{"key":"9737_CR9","doi-asserted-by":"publisher","first-page":"105635","DOI":"10.1016\/j.engappai.2022.105635","volume":"118","author":"X Feng","year":"2023","unstructured":"Feng X, Cai W, Zheng R, Tang L, Zhou J, Wang H, Liao J, Luo B, Cheng W, Wei An, Zhao W, Jing X, Liang P, Yu J, Huang Q (2023) Diagnosis of hepatocellular carcinoma using deep network with multi-view enhanced patterns mined in contrast-enhanced ultrasound data. Eng Appl Artif Intell 118:105635","journal-title":"Eng Appl Artif Intell"},{"key":"9737_CR10","first-page":"1","volume":"40","author":"X Guo","year":"2023","unstructured":"Guo X, Tian C, Liu G, Mi X, Gao D (2023) Diagnostic efficacy of contrast-enhanced ultrasound, dynamic contrast-enhanced MRI combined with tumor markers AFP and DCP for primary hepatocellular carcinoma. Biotechnol Genetic Eng Rev 40:1\u201315","journal-title":"Biotechnol Genetic Eng Rev"},{"issue":"1","key":"9737_CR11","doi-asserted-by":"publisher","first-page":"7924","DOI":"10.1038\/s41598-022-11997-w","volume":"12","author":"R Hu","year":"2022","unstructured":"Hu R, Li H, Horng H, Thomasian NM, Jiao Z, Zhu C, Zou B, Bai HX (2022) Automated machine learning for differentiation of hepatocellular carcinoma from intrahepatic cholangiocarcinoma on multiphasic MRI. Sci Rep 12(1):7924","journal-title":"Sci Rep"},{"issue":"3","key":"9737_CR12","doi-asserted-by":"publisher","first-page":"525","DOI":"10.1093\/comjnl\/bxab162","volume":"66","author":"A Krishan","year":"2023","unstructured":"Krishan A, Mittal D (2023) Multi-class liver cancer diseases classification using CT images. Comput J 66(3):525\u2013539","journal-title":"Comput J"},{"issue":"8","key":"9737_CR13","doi-asserted-by":"publisher","first-page":"4123","DOI":"10.1109\/JBHI.2022.3161466","volume":"26","author":"S Li","year":"2022","unstructured":"Li S, Xie Y, Wang G, Zhang L, Zhou W (2022) Adaptive multimodal fusion with attention guided deep supervision net for grading hepatocellular carcinoma. IEEE J Biomed Health Inform 26(8):4123\u20134131","journal-title":"IEEE J Biomed Health Inform"},{"key":"9737_CR14","doi-asserted-by":"publisher","first-page":"109638","DOI":"10.1016\/j.patcog.2023.109638","volume":"142","author":"Y Li","year":"2023","unstructured":"Li Y, Li S, Ju H, Harada T, Zhang H, Duan T, Wang G, Zhang L, Gu L, Zhou W (2023) Correlated and individual feature learning with contrast-enhanced MR for malignancy characterization of hepatocellular carcinoma. Pattern Recognit 142:109638","journal-title":"Pattern Recognit"},{"issue":"3","key":"9737_CR15","doi-asserted-by":"publisher","first-page":"577","DOI":"10.1007\/s12072-022-10321-y","volume":"16","author":"Z Liu","year":"2022","unstructured":"Liu Z, Liu Y, Zhang W, Hong Y, Meng J, Wang J, Zheng S, Xu X (2022) Deep learning for prediction of hepatocellular carcinoma recurrence after resection or liver transplantation: a discovery and validation study. Hepatol Int 16(3):577\u2013589","journal-title":"Hepatol Int"},{"issue":"5","key":"9737_CR16","doi-asserted-by":"publisher","first-page":"2520","DOI":"10.3390\/s23052520","volume":"23","author":"DA Mitrea","year":"2023","unstructured":"Mitrea DA, Brehar R, Nedevschi S, Lupsor-Platon M, Socaciu M, Badea R (2023) Hepatocellular carcinoma recognition from ultrasound images using combinations of conventional and deep learning techniques. Sensors 23(5):2520","journal-title":"Sensors"},{"issue":"1","key":"9737_CR17","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1038\/s41597-023-01928-3","volume":"10","author":"AW Moawad","year":"2023","unstructured":"Moawad AW, Morshid A, Khalaf AM, Elmohr MM, Hazle JD, Fuentes D, Badawy M, Kaseb AO, Hassan M, Mahvash A, Szklaruk J, Qayyum A, Abusaif A, Bennett WC, Nolan TS, Camp B, Elsayes KM (2023) Multimodality annotated hepatocellular carcinoma data set including pre-and post-TACE with imaging segmentation. Sci Data 10(1):33","journal-title":"Sci Data"},{"issue":"11","key":"9737_CR18","doi-asserted-by":"publisher","first-page":"7883","DOI":"10.1007\/s00330-022-08826-z","volume":"32","author":"J Pan","year":"2022","unstructured":"Pan J, Li W, Gu L, Liu C, Zhang K, Hong G (2022) Performance of adding hepatobiliary phase image in magnetic resonance imaging for detection of hepatocellular carcinoma: a meta-analysis. Eur Radiol 32(11):7883\u20137895","journal-title":"Eur Radiol"},{"issue":"1","key":"9737_CR19","first-page":"51","volume":"3","author":"NS Parra","year":"2023","unstructured":"Parra NS, Ross HM, Khan A, Wu M, Goldberg R, Shah L, Mukhtar S, Beiriger J, Gerber A, Halegoua-DeMarzio D (2023) Advancements in the diagnosis of hepatocellular carcinoma. Int J Transl Med 3(1):51\u201365","journal-title":"Int J Transl Med"},{"key":"9737_CR20","doi-asserted-by":"publisher","DOI":"10.2147\/JHC.S400166","author":"X Qin","year":"2023","unstructured":"Qin X, Hu X, Xiao W, Zhu C, Ma Q, Zhang C (2023) Preoperative evaluation of hepatocellular carcinoma differentiation using contrast-enhanced ultrasound-based deep-learning radiomics model. J Hepatocell Carcinoma. https:\/\/doi.org\/10.2147\/JHC.S400166","journal-title":"J Hepatocell Carcinoma"},{"key":"9737_CR21","doi-asserted-by":"publisher","DOI":"10.1007\/s12072-023-10511-2","author":"WF Qu","year":"2023","unstructured":"Qu WF, Tian MX, Lu HW, Zhou YF, Liu WR, Tang Z, Shi YH (2023) Development of a deep pathomics score for predicting hepatocellular carcinoma recurrence after liver transplantation. Hepatol Int. https:\/\/doi.org\/10.1007\/s12072-023-10511-2","journal-title":"Hepatol Int"},{"issue":"5","key":"9737_CR22","doi-asserted-by":"publisher","first-page":"757","DOI":"10.1159\/000531016","volume":"41","author":"J Quek","year":"2023","unstructured":"Quek J, Tan DJH, Chan KE, Lim WH, Ng CH, Ren YP, Koh TK, Teh R, Xiao J, Fu C, Syn N, Teng M, Muthiah M, Fowler KJ, Sirlin CB, Loomba R, Huang DQ (2023) Quality assessment of ultrasound and magnetic resonance imaging for hepatocellular carcinoma surveillance: a systematic review and meta-analysis. Dig Dis 41(5):757\u2013766","journal-title":"Dig Dis"},{"key":"9737_CR23","doi-asserted-by":"publisher","first-page":"104908","DOI":"10.1016\/j.bspc.2023.104908","volume":"85","author":"MY Shams","year":"2023","unstructured":"Shams MY, El-kenawy ESM, Ibrahim A, Elshewey AM (2023) A hybrid dipper throated optimization algorithm and particle swarm optimization (DTPSO) model for hepatocellular carcinoma (HCC) prediction. Biomed Signal Process Control 85:104908","journal-title":"Biomed Signal Process Control"},{"issue":"8","key":"9737_CR24","doi-asserted-by":"publisher","first-page":"2917","DOI":"10.1007\/s00259-022-05742-8","volume":"49","author":"K Sun","year":"2022","unstructured":"Sun K, Shi L, Qiu J, Pan Y, Wang X, Wang H (2022) Multi-phase contrast-enhanced magnetic resonance image-based radiomics-combined machine learning reveals microscopic ultra-early hepatocellular carcinoma lesions. Eur J Nucl Med Mol Imaging 49(8):2917\u20132928","journal-title":"Eur J Nucl Med Mol Imaging"},{"issue":"1","key":"9737_CR25","doi-asserted-by":"publisher","first-page":"e14210","DOI":"10.1002\/acm2.14210","volume":"25","author":"S Tangruangkiat","year":"2024","unstructured":"Tangruangkiat S, Chaiwongkot N, Pamarapa C, Rawangwong T, Khunnarong A, Chainarong C, Sathapanawanthana P, Hiranrat P, Keerativittayayut R, Sungkarat W, Phonlakrai M (2024) Diagnosis of focal liver lesions from ultrasound images using a pretrained residual neural network. J Appl Clin Med Phys 25(1):e14210","journal-title":"J Appl Clin Med Phys"},{"key":"9737_CR26","doi-asserted-by":"publisher","first-page":"105058","DOI":"10.1016\/j.compbiomed.2021.105058","volume":"141","author":"X Wang","year":"2022","unstructured":"Wang X, Wang S, Yin X, Zheng Y (2022) MRI-based radiomics distinguish different pathological types of hepatocellular carcinoma. Comput Biol Med 141:105058","journal-title":"Comput Biol Med"},{"issue":"23","key":"9737_CR27","doi-asserted-by":"publisher","first-page":"5701","DOI":"10.3390\/cancers15235701","volume":"15","author":"Q Wei","year":"2023","unstructured":"Wei Q, Tan N, Xiong S, Luo W, Xia H, Luo B (2023) Deep learning methods in medical image-based hepatocellular carcinoma diagnosis: a systematic review and meta-analysis. Cancers 15(23):5701","journal-title":"Cancers"},{"key":"9737_CR28","unstructured":"https:\/\/www.kaggle.com\/datasets\/andrewmvd\/lits-png"},{"issue":"6","key":"9737_CR29","doi-asserted-by":"publisher","first-page":"1333","DOI":"10.1002\/jum.16151","volume":"42","author":"MF Xian","year":"2023","unstructured":"Xian MF, Li W, Lan WT, Zeng D, Xie WX, Lu MD, Xian M-F, Lan W-T, Xie W-X, Lu M-D, Huang Y, Wang W (2023) Strategy for accurate diagnosis by contrast-enhanced ultrasound of focal liver lesions in patients not at high risk for hepatocellular carcinoma: a preliminary study. J Ultrasound Med 42(6):1333\u20131344","journal-title":"J Ultrasound Med"},{"issue":"3","key":"9737_CR30","doi-asserted-by":"publisher","first-page":"1512","DOI":"10.1109\/JBHI.2022.3233717","volume":"27","author":"H Zhang","year":"2023","unstructured":"Zhang H, Guo L, Wang J, Ying S, Shi J (2023a) Multi-view feature transformation based SVM+ for computer-aided diagnosis of liver cancers with ultrasound images. IEEE J Biomed Health Inform 27(3):1512\u20131523","journal-title":"IEEE J Biomed Health Inform"},{"key":"9737_CR31","doi-asserted-by":"publisher","first-page":"105126","DOI":"10.1016\/j.bspc.2023.105126","volume":"86","author":"J Zhang","year":"2023","unstructured":"Zhang J, Qiu S, Li Q, Zhou C, Hu Z, Weng J, Sheng X, Dong Q, Ren N (2023b) Hepatocellular carcinoma histopathological images grading with a novel attention-sharing hybrid network based on multi-feature fusion. Biomed Signal Process Control 86:105126","journal-title":"Biomed Signal Process Control"},{"issue":"1","key":"9737_CR32","doi-asserted-by":"publisher","first-page":"55","DOI":"10.3233\/CH-231944","volume":"87","author":"Q Zhao","year":"2024","unstructured":"Zhao Q, Ji Z, Chen Y, Wang K, Qiu Y, Tian X, Zhu Y, Qin H, Han H, Yuan H, Dong Yi, Wang W (2024) Contrast-enhanced ultrasound features of hepatic sarcomatoid carcinoma different from hepatocellular carcinoma. Clin Hemorheol Microcirc 87(1):55\u201365","journal-title":"Clin Hemorheol Microcirc"},{"issue":"1","key":"9737_CR33","doi-asserted-by":"publisher","first-page":"114","DOI":"10.1109\/TUFFC.2021.3110590","volume":"69","author":"J Zhou","year":"2021","unstructured":"Zhou J, Pan F, Li W, Hu H, Wang W, Huang Q (2021) Feature fusion for diagnosis of atypical hepatocellular carcinoma in contrast-enhanced ultrasound. IEEE Trans Ultrason Ferroelectr Freq Control 69(1):114\u2013123","journal-title":"IEEE Trans Ultrason Ferroelectr Freq Control"}],"container-title":["Evolving Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12530-025-09737-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12530-025-09737-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12530-025-09737-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T10:44:40Z","timestamp":1764845080000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12530-025-09737-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,22]]},"references-count":33,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2025,12]]}},"alternative-id":["9737"],"URL":"https:\/\/doi.org\/10.1007\/s12530-025-09737-2","relation":{},"ISSN":["1868-6478","1868-6486"],"issn-type":[{"value":"1868-6478","type":"print"},{"value":"1868-6486","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,22]]},"assertion":[{"value":"2 February 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 August 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 September 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"113"}}