论文标题
用于自动头骨缺陷修复和颅内植入物设计的在线平台
An Online Platform for Automatic Skull Defect Restoration and Cranial Implant Design
论文作者
论文摘要
我们引入了一个用于颅内植入物设计的全自动系统，这是颅骨成形术操作中的常见任务。该系统目前已集成在StudierFenster（http://studierfensster.tugraz.at/）中，这是一个用于医学成像应用程序的在线基于云的医学图像处理平台。通过深度学习算法增强，系统会自动恢复头骨的缺失部分（即颅骨形状完成），并通过从完成的头骨中减去有缺陷的头骨来生成所需的植入物。可以通过系统的浏览器接口直接以立体光刻（.STL）格式下载生成的植入物。然后可以将植入物模型发送到3D打印机，以进行机车植入物制造。此外，由于标准格式，用户可以随后将模型加载到另一项应用程序中，以便在必要时进行后处理。这种自动颅内植入物设计系统可以集成到临床实践中，以改善与颅骨缺陷修复有关的当前例行程序（例如，颅骨成形术）。我们的系统虽然目前仅用于教育和研究使用，但可以看作是添加剂制造的应用，用于快速，患者特定的植入物设计。
We introduce a fully automatic system for cranial implant design, a common task in cranioplasty operations. The system is currently integrated in Studierfenster (http://studierfenster.tugraz.at/), an online, cloud-based medical image processing platform for medical imaging applications. Enhanced by deep learning algorithms, the system automatically restores the missing part of a skull (i.e., skull shape completion) and generates the desired implant by subtracting the defective skull from the completed skull. The generated implant can be downloaded in the STereoLithography (.stl) format directly via the browser interface of the system. The implant model can then be sent to a 3D printer for in loco implant manufacturing. Furthermore, thanks to the standard format, the user can thereafter load the model into another application for post-processing whenever necessary. Such an automatic cranial implant design system can be integrated into the clinical practice to improve the current routine for surgeries related to skull defect repair (e.g., cranioplasty). Our system, although currently intended for educational and research use only, can be seen as an application of additive manufacturing for fast, patient-specific implant design.
