Suppr超能文献

在原始空间中进行交互式曲线重格式化。

Interactive curvilinear reformatting in native space.

机构信息

Department of Computer Engineering and Industrial Automation, School of Electrical and Computer Engineering, University of Campinas, DCA - FEEC - Unicamp, Av. Albert Einstein, 400, Cidade Universitaria Zeferino Vaz, Distrito Barao Geraldo, Campinas - SP 13083-852 - Brasil.

出版信息

IEEE Trans Vis Comput Graph. 2012 Feb;18(2):299-308. doi: 10.1109/TVCG.2011.40.

Abstract

Curvilinear reformatting of 3D magnetic resonance imaging data has been recognized by the medical community as a helpful noninvasive tool for displaying the cerebral anatomy. It consists of automatically creating, with respect to a reference surface, a series of equidistant curvilinear slices at progressively deeper cuts. In comparison with planar slices, it allows more precise localization of lesions and identification of subtle structural abnormalities. However, current curvilinear reformatting tools either rely on the time-consuming manual delineation of guiding curves on 2D slices, or require costly automatic brain segmentation procedures. In addition, they extract the skin and skull, impeding a precise topographic correlation between the location of the brain lesion and skin surface. This impairs planning of craniotomy for neurosurgery, and of the appropriate implantation of electrodes for intracranial electroencephalography in presurgical evaluation. In this work, we present a novel approach based on direct manipulation of the visualized volume data. By using a 3D painting metaphor, the reference surface can be defined incrementally, according to the principle that the user interacts with what she/he sees. As a response, an animation of the reformatting process is displayed. The focus of this paper is a new volume tagging algorithm behind user interactions. It works at an interactive frame rate on current graphics hardware.

摘要

三维磁共振成像数据的曲线重建已被医学界公认为一种有助于显示大脑解剖结构的无创工具。它包括根据参考面自动创建一系列等距的曲线切片,以进行逐步深入的切割。与平面切片相比,它可以更精确地定位病变并识别细微的结构异常。然而,目前的曲线重建工具要么依赖于在 2D 切片上手动绘制引导曲线,这既耗时又费力,要么需要昂贵的自动脑部分割过程。此外,这些工具还提取了皮肤和颅骨,这阻碍了大脑病变位置与皮肤表面之间的精确地形相关性。这会影响神经外科开颅手术的计划,以及术前评估中颅内脑电图电极的适当植入。在这项工作中,我们提出了一种基于直接操作可视化体积数据的新方法。通过使用 3D 绘画隐喻,可以根据用户与所见内容交互的原则,逐步定义参考面。作为响应,会显示重新格式化过程的动画。本文的重点是用户交互背后的一种新的体积标记算法。它可以在当前的图形硬件上以交互帧率运行。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验