论文标题
基于网络的工具的设计和开发，用于在血管造影图像中介绍解剖主动脉
Design and Development of a Web-based Tool for Inpainting of Dissected Aortae in Angiography Images
论文作者
论文摘要
医学成像是主动脉夹层诊断和评估（AD）的重要工具；主动脉的严重疾病，可能导致威胁生命的主动脉损伤。 AD患者需要对主动脉夹诊诊断后的主动脉肿大和疾病进展的终身医学监测。由于缺乏医学研究中的“健康删除”图像对，因此使用介质技术的应用为通过从解剖主动脉到健康主动脉进行虚拟回归而产生它们的替代来源。研究疾病起源的一种间接方法。所提出的介绍工具结合了一个神经网络，该网络接受了介入主动脉解剖的任务，并易于使用的用户界面。为了实现这一目标，在Studierfenster的3D医疗图像查看器（www.studierfensster.at）中已集成了内部工具。通过将工具设计为Web应用程序，我们简化了神经网络的使用情况，并减少了初始学习曲线。
Medical imaging is an important tool for the diagnosis and the evaluation of an aortic dissection (AD); a serious condition of the aorta, which could lead to a life-threatening aortic rupture. AD patients need life-long medical monitoring of the aortic enlargement and of the disease progression, subsequent to the diagnosis of the aortic dissection. Since there is a lack of 'healthy-dissected' image pairs from medical studies, the application of inpainting techniques offers an alternative source for generating them by doing a virtual regression from dissected aortae to healthy aortae; an indirect way to study the origin of the disease. The proposed inpainting tool combines a neural network, which was trained on the task of inpainting aortic dissections, with an easy-to-use user interface. To achieve this goal, the inpainting tool has been integrated within the 3D medical image viewer of StudierFenster (www.studierfenster.at). By designing the tool as a web application, we simplify the usage of the neural network and reduce the initial learning curve.
