Artificial intelligence in imaging diagnosis of liver tumors: current status and future prospects.
Liver cancer remains a significant global health concern, ranking as the sixth most common malignancy and the third leading cause of cancer-related deaths worldwide. Medical imaging plays a vital role in managing liver tumors, particularly hepatocellular carcinoma (HCC) and metastatic lesions. Howev...
| Publicado en: | Abdominal Radiology Vol. 51; no. 1; pp. 446 - 458 |
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| Autores principales: | , , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Jan2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=191138663&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 191138663 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 2366004X JT14 jtl: Abdominal Radiology issn: 2366004X maglogo: N pubinfo: dt: Jan2026 vid: 51 iid: 1 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 191138663 186034086 10.1007/s00261-025-05059-8 191138663 ppf: 446 ppct: 12 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Artificial intelligence in imaging diagnosis of liver tumors: current status and future prospects. aug: au: Hori, Masatoshi Suzuki, Yuki Sofue, Keitaro Sato, Junya Nishigaki, Daiki Tomiyama, Miyuki Nakamoto, Atsushi Murakami, Takamichi Tomiyama, Noriyuki affil: https://ror.org/035t8zc32 Department of Artificial Intelligence in Diagnostic Radiology, The University of Osaka Graduate School of Medicine, 2-2, Yamadaoka, 565-0871, Suita, Japan sug: ab: Liver cancer remains a significant global health concern, ranking as the sixth most common malignancy and the third leading cause of cancer-related deaths worldwide. Medical imaging plays a vital role in managing liver tumors, particularly hepatocellular carcinoma (HCC) and metastatic lesions. However, the large volume and complexity of imaging data can make accurate and efficient interpretation challenging. Artificial intelligence (AI) is recognized as a promising tool to address these challenges. Therefore, this review aims to explore the recent advances in AI applications in liver tumor imaging, focusing on key areas such as image reconstruction, image quality enhancement, lesion detection, tumor characterization, segmentation, and radiomics. Among these, AI-based image reconstruction has already been widely integrated into clinical workflows, helping to enhance image quality while reducing radiation exposure. While the adoption of AI-assisted diagnostic tools in liver imaging has lagged behind other fields, such as chest imaging, recent developments are driving their increasing integration into clinical practice. In the future, AI is expected to play a central role in various aspects of liver cancer care, including comprehensive image analysis, treatment planning, response evaluation, and prognosis prediction. This review offers a comprehensive overview of the status and prospects of AI applications in liver tumor imaging. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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