A recent study reported the development and validation of the Liver Artificial Intelligence Diagnosis System (LiAIDS), a fully automated system that integrates deep learning for the diagnosis of liver lesions on the basis of contrast-enhanced CT scans and clinical information. This tool improved ...
Radiology 217: 750–756 Ueda K, Matsui O, Kawamori Y, et al. (1998) Differentiation of hypervascular hepatic pseudolesions from hepatocellular carcinoma: value of single level dynamic CT during hepatic arteriography. JCAT 22:703–708 About this Chapter Title Arterioportal Shunt I — Early ...
- 《Radiology》 被引量: 573发表: 2008年 Diffusion-weighted MR imaging of the liver: distinguishing hepatic abscess from cystic or necrotic tumor. Background: We evaluated the ability of diffusion-weighted (DW) magnetic resonance (MR) imaging to differentiate between hepatic abscess and cystic or ...
There were 5 false-negative lesions, all of which exhibited lower metabolic levels than the liver. However, pathological examination confirmed them as actual prostate cancer cases. There were 2 false-positive lesions, with one exhibiting higher metabolic levels than the salivary glands and the other...
US-guided percutaneous biopsy of focal liver lesions (FLL) is a classic interventional procedure performed by almost all radiology units. Typically, an inc... Torben,Lorentzen,Christian,... - 《Ultrasound International Open》 被引量: 0发表: 2019年 CAPILLARY HEMORRHAGE INDUCED BY CONTRAST-ENHANCED ...
Early-enhancing non-neoplastic lesions on gadolinium-enhanced MRI of the liver. Clin Radiol 2003;58:778 -786.Kanematsu M,Kondo H,Semelka RC,et al.Early-enhancing non-neoplastic lesions on gadolinium-enhanced MRI of the liver. Clinical Radiology . 2003...
Clinical RadiologyKanematsu M, Kondo H, Semelka RC, et al. Early-enhancing non-neoplastic lesions on gadolinium-enhanced MRI of the liver. Clin Radiol 2003; 58:778 -786.Goshima S, Kanematsu M, Matsuo M, Kondo H, Yokoyama R, Hoshi H, Moriyama N. Early-enhancing nonneoplastic lesions on ...
doi:10.1016/j.jvir.2021.04.014Mohamed ElboraeyZlatko DevcicS Ali MontazeriXi LiBeau B ToskichJournal of vascular and interventional radiology: JVIR
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Bera, K., Braman, N., Gupta, A., Velcheti, V. & Madabhushi, A. Predicting cancer outcomes with radiomics and artificial intelligence in radiology.Nat. Rev. Clin. Oncol.19, 132–146 (2021). Hughes, J. W. et al. Deep learning evaluation of biomarkers from echocardiogram videos.EBioMe...