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计算机辅助在CT肺动脉造影中利用雪橇算法和多实例分类检测肺栓塞。

Computer aided detection of pulmonary embolism with tobogganing and mutiple instance classification in CT pulmonary angiography.

作者信息

Liang Jianming, Bi Jinbo

机构信息

Computer Aided Diagnosis and Therapy Siemens Medical Solutuions USA, Inc., Malvern, PA 19355, USA.

出版信息

Inf Process Med Imaging. 2007;20:630-41. doi: 10.1007/978-3-540-73273-0_52.

DOI:10.1007/978-3-540-73273-0_52
PMID:17633735
Abstract

Pulmonary embolism (PE) is a very serious condition causing sudden death in about one-third of the cases. Treatment with anti-clotting medications is highly effective but not without complications, while diagnosis has been missed in about 70% of the cases. A major clinical challenge, particularly in an Emergency Room, is to quickly and correctly diagnose patients with PE and then send them on to therapy. Computed tomographic pulmonary angiography (CTPA) has recently emerged as an accurate diagnostic tool for PE, but each CTPA study contains hundreds of CT slices. The accuracy and efficiency of interpreting such a large image data set is complicated by various PE look-alikes and also limited by human factors, such as attention span and eye fatigue. In response to this challenge, in this paper, we present a fast yet effective approach for computer aided detection of pulmonary embolism in CTPA. Our proposed approach is capable of detecting both acute and chronic pulmonary emboli with a distinguished feature of incrementally reporting any detection immediately once becoming available during searching, offering real-time support and achieving 80% sensitivity at 4 false positives. This superior performance is contributed to our novel algorithms (concentration oriented tobogganing and multiple instance classification) introduced in this paper for candidate detection and false positive reduction.

摘要

肺栓塞(PE)是一种非常严重的病症,约三分之一的病例会导致猝死。使用抗凝血药物治疗非常有效,但并非没有并发症,而且约70%的病例会漏诊。一个主要的临床挑战,尤其是在急诊室,是快速、正确地诊断肺栓塞患者,然后将他们送去治疗。计算机断层扫描肺动脉造影(CTPA)最近已成为一种用于诊断肺栓塞的准确工具,但每次CTPA检查都包含数百张CT切片。解释如此大量的图像数据集的准确性和效率因各种类似肺栓塞的情况而变得复杂,同时也受到人为因素的限制,如注意力持续时间和眼睛疲劳。为应对这一挑战,在本文中,我们提出了一种快速且有效的方法,用于在CTPA中进行计算机辅助检测肺栓塞。我们提出的方法能够检测急性和慢性肺栓塞,其显著特点是在搜索过程中一旦检测到就立即增量报告,提供实时支持,并在4例假阳性的情况下实现80%的灵敏度。这种卓越的性能得益于我们在本文中引入的用于候选检测和减少假阳性的新颖算法(浓度导向的拖尾法和多实例分类)。

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