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首页> 外文期刊>Electronic Letters on Computer Vision and Image Analysis: ELCVIA >Tracheal Structure Characterization using Geometric and Appearance Models for Efficient Assessment of Stenosis in Videobronchoscopy
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Tracheal Structure Characterization using Geometric and Appearance Models for Efficient Assessment of Stenosis in Videobronchoscopy

机译：气管结构表征使用几何模型和外观模型有效评估电子支气管镜狭窄

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摘要

Recent advances in endoscopic devices have increased their use for minimal invasive diagnostic and intervention?procedures. Among all endoscopic modalities, bronchoscopy is one of the most frequent with around 261?millions of procedures per year. Although the use of bronchoscopy is spread among clinical facilities it presents?some drawbacks, being the visual inspection for the assessment of anatomical measurements the most prevalent?of them. In particular, inaccuracies in the estimation of the degree of stenosis (the percentage of obstructed?airway) decreases its diagnostic yield and might lead to erroneous treatments. An objective computation of?tracheal stenosis in bronchoscopy videos would constitute a breakthrough for this non-invasive technique and?a reduction in treatment cost. This thesis settles the first steps towards on-line reliable extraction of anatomical information from videobronchoscopy?for computation of objective measures. In particular, we focus on the computation of the degree?of stenosis, which is obtained by comparing the area delimited by a healthy tracheal ring and the stenosed?lumen. In this sense, we have to consider that reliable extraction of?airway structures in interventional videobronchoscopy is a challenging task. This is mainly due to the large?variety of acquisition conditions (positions and illumination), devices (different digitalizations) and in videos acquired at the operating room the unpredicted presence of surgical devices (such as probe ends). This thesis?contributes to on-line stenosis assessment in several ways. We propose a parametric strategy for the extraction?of lumen and tracheal rings regions based on the characterization of their geometry and appearance that guide?a deformable model. The geometric and appearance characterization is based on a physical model describing?the way bronchoscopy images are obtained and includes local and global descriptions. In order to ensure?a systematic applicability we present a statistical framework to select the optimal parameters of our method.?Experiments perform on the first public annotated database, show that the performance of our method is comparable?to the one provided by clinicians and its computation time allows for a on-line implementation in the?operating room.
机译：内窥镜设备的最新进展增加了其在微创诊断和干预过程中的应用。在所有内窥镜检查方法中，支气管镜检查是最常见的一种，每年约有2.61亿次手术。尽管在临床设施中广泛使用支气管镜，但它仍存在一些缺陷，其中最普遍的是视觉检查，以评估解剖学测量结果。特别是，狭窄程度（气道阻塞的百分比）的估计不准确会降低其诊断率，并可能导致治疗错误。支气管镜录像中气管狭窄的客观计算将构成这种非侵入性技术的突破，并降低治疗成本。本文确定了从视频支气管镜在线可靠地提取解剖信息以计算客观指标的第一步。特别地，我们专注于狭窄程度的计算，该狭窄程度是通过比较由健康的气管环和狭窄的管腔界定的面积而获得的。从这个意义上讲，我们必须考虑在介入性视频支气管镜检查中可靠地提取气道结构是一项艰巨的任务。这主要是由于采集条件（位置和照明），设备（数字化程度不同）的多样性以及在手术室采集的视频中外科设备（例如探头末端）的存在无法预测的。本论文以多种方式有助于在线狭窄评估。我们提出了一种基于管腔和气管环区域提取的参数化策略，该策略基于其指导可变形模型的几何形状和外观特征。几何和外观特征是基于描述支气管镜图像获取方式的物理模型，并包括局部和全局描述。为了确保“系统的适用性”，我们提供了一个统计框架来选择我们方法的最佳参数。“实验在第一个公开注释的数据库上进行，表明我们方法的性能可与临床医生及其提供的方法相媲美”。计算时间允许在手术室中进行在线实施。

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