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基于时空分析的手术场景三维重建方法研究
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Abstract:
内窥镜图像的深度估计与手术场景三维重建是微创手术中提高外科医师手术效率的关键因素。本文提出一种基于时空分析的手术场景三维重建方法，深度估计网络采用编码器–解码器结构，编码器使用ResNet34模块、改进的SAB注意力机制、改进的FPN模块以及特征增强模块；解码器通过上采样获取图像的深度信息和位姿信息，实现内窥镜图像的准确深度估计。在跟踪重建方面，通过时空跟踪优化相机位姿，将空间维度的深度信息与时间维度相结合，通过时空分析与融合，还原手术场景的三维结构。评估采用Hamlyn公共数据集，实验结果表明本文所提方法可有效提高内窥镜图像深度估计的准确性，同时通过与时间维度的深度信息融合，可准确还原手术场景的三维信息，进一步辅助外科医师实现术中精准导航。
Depth estimation of endoscopic image and 3D reconstruction of surgical scene are key factors to improve surgical efficiency of surgeons in minimally invasive surgery. In this paper, a 3D recon-struction method of surgical scene based on spatiotemporal analysis is proposed, and the proposed network is designed as an encoder-decoder structure. The encoder uses ResNet34 module, im-proved SAB attention mechanism, improved FPN module and feature enhancement module, and the decoder obtains the depth information and pose information of the image through up-sampling, so as to realize accurate depth estimation of the endoscope image. In terms of tracking and recon-struction, the camera pose is optimized through spatiotemporal tracking, the depth information of the spatial dimension is combined with the time dimension, and the three-dimensional structure of the surgical scene is restored through spatiotemporal analysis and fusion. Hamlyn public dataset was used for evaluation, and experimental results show that the method proposed in this paper could effectively improve the accuracy of depth estimation of endoscopic images. At the same time, three-dimensional information of surgical scene could be accurately restored through fusion with depth information and time dimension to assist surgeons to achieve accurate intraoperative navi-gation.
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