基于鼠标轨迹语义理解的医学影像阅片交互意图识别  

Interactive intention recognition of medical image reviewing based on semantic understanding of mouse trajectory

作　　者：杨晨希 乔栋 牛怡 崔磊[1] 冯筠[1] YANG Chenxi;QIAO Dong;NIU Yi;CUI Lei;FENG Jun(School of Information Science and Technology,Northwest University,Xi’an 710127,China;Yuncheng Central Hospital,Yuncheng 044000,China)

机构地区：[1]西北大学信息科学与技术学院,陕西西安710127 [2]运城市中心医院,山西运城044000

出　　处：《西北大学学报（自然科学版）》2023年第3期387-400,共14页Journal of Northwest University（Natural Science Edition）

基　　金：国家自然科学基金面上项目(62073260)。

摘　　要：由于诊断成像研究的数量及复杂度不断增加,现影像科医生日常阅片任务繁重、工作负担大,为影像科医生减轻阅片负担、帮助其提高诊断效率已成为各界关注的重点。对医生影像阅片过程中的交互意图进行识别与理解,可用于开发能够提供自适应工具、优化用户工作流程的新型智能影像阅片系统,以帮助医生更高效、更准确地进行数字影像阅片任务。目前,医生进行医学影像阅片仍然主要使用基于鼠标输入的图形用户界面,为此,提出一种基于鼠标轨迹语义理解的医学影像阅片交互意图识别方法。首先,对鼠标交互轨迹进行语义分段;然后,对分段后的鼠标轨迹子序列运用逻辑推理与监督学习的方法进行交互行为语义注释。在自建的鼠标交互轨迹数据集上对所提方法进行验证,该交互意图识别方法在[0.3∶0.8∶0.1]的TIoU阈值下平均识别召回率、精确率及F均值分别达到86.7%、83.1%和85.4%。结果表明该方法可以有效地依据隐式鼠标交互数据实现医学影像阅片交互意图识别,证实了基于鼠标轨迹语义理解的交互意图识别方法在医学影像辅助阅片研究领域中的可行性及有效性。Due to the increasing number and complexity of diagnostic imaging studies,radiologists are now faced with a heavy workload in their daily image reviewing task.It has become a major concern to reduce the burden of image reviewing process for radiologists and help them improve the efficiency of diagnosis.The recognition and understanding of interactive intent during radiologists image review can be used to develop new intelligent review systems that can provide adaptive tools and optimize user workflow to help radiologists perform digital image review tasks more efficiently and accurately.Currently,radiologists still primarily use a graphical user interface based on mouse input for medical image reviewing.To this end,this paper proposes an intention understanding method of medical image reviewing based on mouse interaction trajectories.Firstly,semantic segmentation of mouse interaction trajectories is performed,and then the semantic annotation of mouse interaction behaviors is implemented based on logical reasoning and supervised learning for the segmented trajectory subsequences.The method is validated on a self-built mouse trajectory dataset under the TIoU threshold of[0.3∶0.8∶0.1],and the average recall,precision and F-score of the method reach 86.7%,83.1%and 85.4%,respectively.The results show that the method can effectively identify the interactive intention based on the implicit mouse interaction data,which confirms the feasibility and effectiveness of the interactive intention recognition method based on semantic understanding of mouse interaction trajectories in the field of medical images assisted reviewing research.

关 键 词：交互意图 鼠标交互轨迹 轨迹语义理解 医学影像诊断 人机交互 

分 类 号：TP391.3[自动化与计算机技术—计算机应用技术]