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作 者:段永飞 高继学[2] 倪建鑫 严奉奇 郭佳恒 王东升 DUAN Yong-fei;GAO Ji-xue;NI Jian-xin;YAN Feng-qi;GUO Jia-heng;WANG Dong-sheng(Medical College of Yan'an University,Yan'an 716000,Shaanxi,China;Department of Urology,the Affiliated Hospital of Yan'an University,Yan'an 716000,Shaanxi,China;Urology and Kidney Hospital of Xi'an People's Hospital,Xi'an 710004,Shaanxi,China;Department of Urology,the Second Affiliated Hospital of the Air Force Medical University,Xi'an 710038,Shaanxi,China;Clinical Medical College of Xi'an Medical University,Xi'an 710021,Shaanxi,China)
机构地区:[1]延安大学医学院,陕西延安716000 [2]延安大学附属医院泌尿外科,陕西延安716000 [3]西安市人民医院泌尿肾脏病院,陕西西安710004 [4]空军军医大学第二附属医院泌尿外科,陕西西安710038 [5]西安医学院临床医学院,陕西西安710021
出 处:《医学信息》2023年第11期171-174,共4页Journal of Medical Information
基 金:国家自然科学基金资助项目(编号:82002686)。
摘 要:结节性硬化症相关肾血管平滑肌脂肪瘤(TSC-RAML)是一种罕见的良性实体“三相”肿瘤,破裂出血风险威胁着患者的生命安全。三维立体图像清晰、直观的特点可以很好的用来观察病变、分析肿瘤解剖和预测患者预后。图像分割技术是三维成像的关键步骤,传统分割技术的精度及效率均难以达到实际需求,随着人工智能(AI)的出现,智能化医学影像分割技术在临床中取得快速发展,可有效提高图像分割的精度。本文就智能化学习模型的现状及在TSC-RAML诊疗中的应用进行阐述。Tuberous sclerosis complex-associated renal angiomyolipoma(TSC-RAML)is a rare benign solid"three-phase"tumor.The risk of rupture and bleeding threatens the life safety of patients.The clear and intuitive characteristics of three-dimensional images can be well used to observe lesions,analyze tumor anatomy and predict the prognosis of patients.Image segmentation technology is a key step of three-dimensional imaging,and the accuracy and efficiency of traditional segmentation technology are difficult to meet the actual needs.With the emergence of artificial intelligence(AI),intelligent medical image segmentation technology has achieved rapid development in clinic in recent years,which can effectively improve the accuracy of image segmentation.This paper expounds the current situation of intelligent learning model and its application in TSC-RAML diagnosis and treatment.
关 键 词:人工智能 机器学习 深度学习 结节性硬化症相关肾血管平滑肌脂肪瘤
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