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多任务深度学习用于通过双参数MRI对子宫内膜癌的自动细分和预后分层

Ruixin Yan1, Ximiao Zhang2, Qiqi Cao3

  • 1Department of Radiology, State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University Third Hospital, Beijing, China.

Journal of magnetic resonance imaging : JMRI
|June 19, 2025
PubMed
概括

深度学习框架准确地对子宫内膜癌 (EC) 进行细分,并使用MRI对阶段和入侵等预后因素进行分类,以帮助治疗规划.

关键词:
这是子宫内膜癌的癌症.多任务深度学习预后的分类预测的分类.细分化 细分化的细分化

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Introduction:Magnetic Resonance Imaging, or MRI, can include a specialized imaging technique of the urinary system known as Magnetic Resonance Urography (MRU). This radiation-free technique uses strong magnetic fields and radio waves to produce detailed images with the help of a computer. MRU is particularly effective for visualizing fluid-filled structures like the kidneys, ureters, and bladder.Applications of MRI in the Genitourinary SystemKidneys and Ureters: MRI detects tumors, cysts,...