3D Cerebral vessel location for surgical planning

描述（来自申请人摘要的逐字逐句）：该提案是一项竞争性的 更新3D脑内血管成像的补助金。我们打算建立 通过提供临床上有用的，象征性的描述， 供应血管性CNS肿瘤的血管，包括实体瘤和 动静脉畸形（AVM）。对于外科医生和 介入医生，提供一个3D地图将是非常有价值的， 包含肿瘤边缘，显示了3D父子血管 连接信息，显示动脉和 AVM中的静脉，并且容易分离供应肿瘤的血管分支 供应正常大脑的分支这些信息是那些 最需要知道的事此类信息不能直接提供给 临床医生通过任何当前的成像方法。 该提案的具体目标包括：1）实体肿瘤的分割 2）从磁共振血管造影（MRA）中分割AVM， MR，3）MR与MRA数据的配准，4）血管成像方法的发展 剥离以分离动脉和静脉，并描绘出 分支（和分支）仅供应肿瘤，并且供应大脑，以及5） 测试我们方法的准确性和实用性。 除了临床目标外，该提案还旨在满足一些 计算机视觉研究中的挑战，包括使用 线索范围，基于统计图谱的命名血管定义，以及 自动定义血管分支点。我们提出的方法是 在其他地方是不可用的，对临床医生应该是非常有用的。我们提出 一些研究来评估我们方法的准确性和实用性，以及 我们还提出了新的可视化方法，以表明我们的不确定性， 图像对象的符号描述。

DESCRIPTION (Verbatim from Applicant's Abstract): This proposal is a competing renewal of a grant on 3D intracerebral vascular imaging. We intend to build upon our earlier work by providing a clinically useful, symbolic description of blood vessels supplying vascular CNS tumors, including both solid tumors and arteriovenous malformations (AVMs). For both the surgeon and the interventionalist, it would be enormously valuable to provide a 3D map that contains the tumor margins, that illustrates 3D parent-child vascular connectivity information, that shows the relationship between arteries and veins in AVMs, and that readily segregates vascular branches supplying a tumor from branches supplying normal brain. These kinds of information are those that the clinican most needs to know. Such information is not directly available to clinicians by any current imaging methodology. The specific aims of this proposal include: 1) segmentation of solid tumors from MR, 2) segmentation of AVMs from magnetic resonance angiograms (MRA) and MR, 3) registration of MR with MRA data, 4) development of methods of vascular desbription to separate arteries from veins and to delineate which arterial branches (and descendents) supply only tumor and which supply brain, and 5) tests of the accuracy and utility of our methodology. In addition to its clinical goals, this proposal aims to meet a number of challenges in computer vision research, including tumor segmentation using a range of cues, a statistical atlas based definition of named vessels, and automated definition of vessel branchpoints. The methods we propose are unavailable elsewhere and should be profoundly useful to clinicians. We propose a number of studies to evaluate the accuracy and utility of our approach, and we also propose new visualization methods to indicate the uncertainty of our symbolic descriptions of image objects.