Bricault I, Ferrettio G, Cinquin P
TIMC-IMAG, Institut Albert Bonniot, La Tronche, France.
J Image Guid Surg. 1995;1(4):217-25. doi: 10.1002/(SICI)1522-712X(1995)1:4<217::AID-IGS4>3.0.CO;2-D.
The introduction of spiral computed tomography (CT) of the thoracic cavity has allowed the development of new visualization tools. These tools provide a three-dimensional (3-D) endoluminal reconstruction of the tracheobronchial tree, as it would be viewed through a fibroscopic instrument. However, 3-D reconstruction techniques cannot replace conventional fibroscopy, which remains indispensable for obtaining histological samples. Furthermore, when CT-detected mediastinal or parenchymal lesions are not seen during fiberoptic bronchoscopy, guiding transbronchial needle biopsy is a major challenge. Computer-guided transbronchial biopsy involves the fusion of image data from both CT slices and bronchoscopic video sequences. This fusion is described in this paper in two parts. First, we present a segmentation process, using mathematical morphology operators, in order to analyze the video sequence and localize the bronchoscopic camera within the tracheobronchial tree. Second, we present tools used to match this localization knowledge with CT data. Finally, we produce images that create a bronchoscopic augmented reality, using elements extracted from the CT examination.
胸腔螺旋计算机断层扫描(CT)的引入催生了新的可视化工具。这些工具可对气管支气管树进行三维(3-D)腔内重建,就如同通过纤维镜仪器所看到的那样。然而,三维重建技术无法取代传统的纤维镜检查,获取组织样本时纤维镜检查仍然不可或缺。此外,当在纤维支气管镜检查中未发现CT检测到的纵隔或实质病变时,引导经支气管针吸活检是一项重大挑战。计算机引导的经支气管活检涉及CT切片和支气管镜视频序列的图像数据融合。本文分两部分描述这种融合。首先,我们提出一种使用数学形态学算子的分割过程,以分析视频序列并在气管支气管树内定位支气管镜摄像头。其次,我们介绍用于将此定位知识与CT数据匹配的工具。最后,我们利用从CT检查中提取的元素生成创建支气管镜增强现实的图像。