计算机科学 ›› 2020, Vol. 47 ›› Issue (6A): 172-175.doi: 10.11896/JsJkx.190500154
祁宝莲1, 3, 钟坤华1, 2, 3, 陈芋文1, 2, 3
QI Bao-lian1, 3, ZHONG Kun-hua1, 2, 3 and CHEN Yu-wen1, 2, 3
摘要: 实时鲁棒的开放性外科手术视频流程自动识别检测将是未来人工智能医疗手术室的核心组成部分,这一关键技术结合其他AI(Artificial Intelligence)技术就可以帮助医护人员自动化、智能化地完成多项术中的常规活动。利用人工智能和计算机视觉的方法进行手术流程识别检测需要对大量的数据进行学习,为了训练这种方法,需要大量地标记手术视频数据,然而在医学领域,对外科手术视频数据的标记需要专家知识,收集足够数量的标记外科手术视频数据是困难且耗时的。因此,文中以腹腔镜胆囊切除术视频数据为研究对象,通过半监督学习方法卷积自编码器对视频进行空间特征提取,结合从同视频上下文中的一对视频帧进行时序特征提取,将非结构化的手术视频数据结构化,从而构建低层手术视频特征到高层外科手术流程语义之间的桥梁,以低代价实现对手术视频流程的智能化识别检测,高效判定手术流程进展。在开源数据集上的实验的结果表明,使用该模型Jacc系数达到71.3%,准确率为86.6%,取得了较好的实验效果。
中图分类号:
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