肾脏头颈肿瘤多影像源数据联合智能挖掘算法教学研究  

Research on the teaching of multi image source data and intelligent mining algorithm for renal head and neck tumor

作　　者：徐阳阳 顾欣 王安妮 周涛 Xu Yangyang;Gu Xin;Wang Annie;Zhou tao(Cancer Hospital Affiliated to Harbin Medical University,Harbin 150081,Heilongjiang Province)

机构地区：[1]哈尔滨医科大学附属肿瘤医院,黑龙江省哈尔滨150081

出　　处：《现代科学仪器》2021年第3期272-276,共5页Modern Scientific Instruments

摘　　要：目的设计一种针对肾脏及头颈部多影像源数据融合挖掘算法模型,并将其应用到高校影像学教学中;方法使用影像检查系统内置软件,将影像三维建模矢量结果转化为点阵结果,使用线性投影法针对磁共振、超声、放射断层扫描等多个模型的三维模型数据进行归一化处理,使用基于卷积多列神经网络的人工智能挖掘算法进行数据融合处理,从而构建多层次三维影像学数据融合模型。对比当前进入大五毕业实习阶段的使用该模型辅助进行专业课及教学的影像学2017级学生和未使用该模型辅助教学的2016级学生进行数据对比。结果2017级学生较2016级学生,专业课成绩、自我主观评价、专业老师主观评价、院方实习导师主观评价结果均有所提升。结论该模型可作为影像学辅助教学体系的重要工具。Objective To design a multi-source data fusion mining algorithm model for kidney and head and neck,and apply it to college imaging teaching;Methods The built-in software of the imaging examination system was used to convert the 3D modeling vector results into lattice results.The linear projection method was used to normalize the 3D model data of magnetic resonance,ultrasound,radiation tomography and other models,and the artificial intelligence mining algorithm based on convolution multi column neural network was used for data fusion processing,so as to construct a multi-level 3D model Image data fusion model.This paper compares the data of 2017 grade imaging students who use the model to assist professional courses and teaching and 2016 grade students who do not use the model to assist teaching.Results Compared with 2016 students,2017 students'professional course scores,subjective self-evaluation,subjective evaluation of professional teachers and subjective evaluation of hospital internship tutors were improved.Conclusion The model can be used as an important tool of image assisted teaching system.

关 键 词：肾脏肿瘤 头颈肿瘤 多影像源融合 人工智能数据挖掘 影像学教学 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]