关键词: coronal section data set human head image virtual operation

来  源:   DOI:10.1177/0145561321989432   PDF(Sci-hub)

Abstract:
UNASSIGNED: The aim of the research is to create an experimental data set of coronal section images of a human head.
UNASSIGNED: The head of a 49-year-old male cadaver was scanned by computed tomography (CT), then perfused with a green filling material via the bilateral common carotid artery, before being frozen and embedded. The head was sectioned along the coronal plane by a computer-controlled 5520 engraving and milling machine, capable of either 0.03-mm or 0.06-mm interspacing. All images were captured with a Canon 5D-Mk III digital camera.
UNASSIGNED: A total of 3854 section images were obtained, each with a resolution of 5760 × 3840 pixels. The number of section images at 0.03- and 0.06-mm interspacing were 1437 and 2417, respectively. All the images were stored in JPG and RAW formats. The image size of each RAW format was about 24.5 MB, whereas for JPG format, the equivalent size was about 5.9 MB. All the RAW and JPG images together occupied 117.35 GB of disk space.
UNASSIGNED: The interspacing of this data set section was thinner than those of any comparable studies, and the image resolution was higher, too. This data set was also the first to take coronal sections of the human head. The data set contains image information from the smallest structures within the human head and can satisfy the needs of future developments and applications, such as the virtual operation training systems for otolaryngology, ophthalmology, stomatology, and neurosurgery, and help develop medical teaching software and maps.
摘要:
研究的目的是创建人类头部的冠状截面图像的实验数据集。
通过计算机断层扫描(CT)扫描了49岁的男性尸体的头部,然后通过双侧颈总动脉灌注绿色填充材料,在被冷冻和嵌入之前。头部由计算机控制的5520雕刻机沿冠状面剖开,能够0.03毫米或0.06毫米的间距。所有图像均使用佳能5D-MkIII数码相机捕获。
共获得3854张截面图像,每个分辨率为5760×3840像素。0.03-mm和0.06-mm间距处的切片图像数量分别为1437和2417。所有图像都以JPG和RAW格式存储。每个RAW格式的图像大小约为24.5MB,而对于JPG格式,等效大小约为5.9MB。所有RAW和JPG图像一起占用117.35GB的磁盘空间。
该数据集部分的间距比任何可比研究的间距都要薄,图像分辨率更高,也是。该数据集也是第一个获取人类头部冠状部分的数据。该数据集包含来自人类头部内最小结构的图像信息,可以满足未来开发和应用的需求,例如耳鼻喉科的虚拟操作培训系统,眼科,口腔医学,和神经外科,并帮助开发医学教学软件和地图。
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