深度哈希用于全球注册手术前CT和视频图像,用于腹腔镜肝脏手术
Hanyuan Zhang1, Sandun Bulathsinhala2, Brian R Davidson2
1UCL Hawkes Institute, Department of Medical Physics and Biomedical Engineering, UCL, UK. hanyuan.zhang.23@ucl.ac.uk.
概括
这项研究引入了一个深度散列框架,用于在腹腔镜肝脏手术中强大启动增强现实 (AR). 该方法成功地将手术前的CT扫描与手术期间的视频结合在一起,改善了AR技术的临床翻译.
科学领域:
- 医疗成像医学成像
- 计算机辅助手术 计算机辅助手术
- 增强现实是一种增强现实.
背景情况:
- 计算机断层扫描 (CT) 对腹腔镜视频的准确记录对于肝脏手术中的增强现实 (AR) 是必不可少的.
- 目前的AR方法需要手动或视图特定的初始化,这阻碍了临床采用.
研究的目的:
- 利用基于内容的图像检索 (CBIR) 框架开发一个强大的,自动初始化方法,用于腹腔镜肝脏手术中CT-to-video注册.
- 克服手动初始化的局限性,并使AR的更广泛的临床翻译成为可能.
主要方法:
- 使用了一个CBIR框架,使用一个深层哈希 (DH) 网络,在三重模式中进行训练.
- 从CT染中提取肝脏轮特征,通过将手术内图像哈希与手术前染相匹配来实现注册.
主要成果:
- 该方法在八次手术的幻影和真实患者数据上得到了验证.
- 在幻影数据上实现了可接受的注册错误,在八名患者中,有七名患者获得了临床相关的对齐.
结论:
- 本研究介绍了深度哈希的第一次适应CT-to-video注册.
- 拟议的框架有效地取代了手动初始化,为在肝脏手术中增加AR的临床使用铺平了道路.
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