MED-EL Elektromedizinische Geräte GesmbH, Innsbruck, Austria.
Hannover Medical School, Dept. Otorhinolaryngology, Hannover Germany.
Sci Data. 2019 Jan 8;6:180297. doi: 10.1038/sdata.2018.297.
Virtual reality surgical simulation of temporal bone surgery requires digitized models of the full anatomical region in high quality and colour information to allow realistic texturization. Existing datasets which are usually based on microCT imaging are unable to fulfil these requirements as per the limited specimen size, and lack of colour information. The OpenEar Dataset provides a library consisting of eight three-dimensional models of the human temporal bone to enable surgical training including colour data. Each dataset is based on a combination of multimodal imaging including Cone Beam Computed Tomography (CBCT) and micro-slicing. 3D reconstruction of micro-slicing images and subsequent registration to CBCT images allowed for relatively efficient multimodal segmentation of inner ear compartments, middle ear bones, tympanic membrane, relevant nerve structures, blood vessels and the temporal bone. Raw data from the experiment as well as voxel data and triangulated models from the segmentation are provided in full for use in surgical simulators or any other application which relies on high quality models of the human temporal bone.
虚拟现实颞骨手术模拟需要高质量的全解剖区域数字化模型和颜色信息,以实现真实的纹理化。现有的数据集通常基于 microCT 成像,由于标本尺寸有限,且缺乏颜色信息,因此无法满足这些要求。OpenEar 数据集提供了一个包含八个人类颞骨三维模型的库,可用于包括颜色数据的手术培训。每个数据集都是基于多模态成像(包括锥形束 CT(CBCT)和微切片)的组合。微切片图像的 3D 重建和随后与 CBCT 图像的配准允许对内耳腔室、中耳骨、鼓膜、相关神经结构、血管和颞骨进行相对高效的多模态分割。实验的原始数据以及分割的体素数据和三角化模型都完整提供,可用于手术模拟器或任何其他依赖于高质量人类颞骨模型的应用程序。