Blood circulation in the human brain is supplied through a network of cerebral arteries. If a clinician suspects a patient has a stroke or other cerebrovascular condition, they order imaging tests. Neuroradiologists visually search the resulting scans for abnormalities. Their visual search tasks correspond to the abstract network analysis tasks of browsing and path following. To assist neuroradiologists in identifying cerebral artery abnormalities, we designed CerebroVis, a novel abstract-yet spatially contextualized-cerebral artery network visualization. In this design study, we contribute a novel framing and definition of the cerebral artery system in terms of network theory and characterize neuroradiologist domain goals as abstract visualization and network analysis tasks. Through an iterative, user-centered design process we developed an abstract network layout technique which incorporates cerebral artery spatial context. The abstract visualization enables increased domain task performance over 3D geometry representations, while including spatial context helps preserve the user's mental map of the underlying geometry. We provide open source implementations of our network layout technique and prototype cerebral artery visualization tool. We demonstrate the robustness of our technique by successfully laying out 61 open source brain scans. We evaluate the effectiveness of our layout through a mixed methods study with three neuroradiologists. In a formative controlled experiment our study participants used CerebroVis and a conventional 3D visualization to examine real cerebral artery imaging data to identify a simulated intracranial artery stenosis. Participants were more accurate at identifying stenoses using CerebroVis (absolute risk difference 13%). A free copy of this paper, the evaluation stimuli and data, and source code are available at osf.io/e5sxt.

中文翻译：

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CerebroVis：设计一个抽象但空间关联的脑动脉网络可视化。

人脑中的血液循环是通过脑动脉网络提供的。如果临床医生怀疑患者患有中风或其他脑血管疾病，他们会要求进行影像学检查。神经放射学家可视地搜索结果扫描的异常情况。他们的视觉搜索任务对应于浏览和路径跟随的抽象网络分析任务。为了帮助神经放​​射科医生识别脑动脉异常，我们设计了CerebroVis，这是一种新颖的，但仍在空间背景下实现的脑动脉网络可视化。在本设计研究中，我们将根据网络理论为脑动脉系统建立新颖的框架和定义，并将神经放射科医生的领域目标表征为抽象的可视化和网络分析任务。通过迭代，以用户为中心的设计过程，我们开发了一种抽象的网络布局技术，该技术结合了脑动脉空间上下文。抽象的可视化功能可以提高3D几何图形表示形式的领域任务性能，同时包含空间上下文有助于保留用户对基本几何图形的思维导图。我们提供网络布局技术和原型脑动脉可视化工具的开源实现。我们通过成功地布局61个开源脑部扫描展示了我们技术的鲁棒性。我们通过与三位神经放射科医生的混合方法研究来评估布局的有效性。在形成性对照实验中，我们的研究参与者使用CerebroVis和常规3D可视化技术检查真实的脑动脉成像数据，以识别模拟的颅内动脉狭窄。参与者使用CerebroVis识别狭窄的准确性更高（绝对风险差异为13％）。可以从osf.io/e5sxt获得此白皮书的免费副本，评估激励和数据以及源代码。