课题基金 / 基金详情

Extending ezBIDS, NiiVue and dcm2niix for user-friendly cloud-based integration and visualization

Extending ezBIDS, NiiVue and dcm2niix for user-friendly cloud-based integration and visualization
扩展 ezBIDS、NiiVue 和 dcm2niix,以实现用户友好的基于云的集成和可视化
批准号:
10724895
负责人:
Christopher Rorden
金额:
$203.96万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-08-01 至 2026-07-31

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中文摘要
翻译
项目总结/摘要 基于云的分析和易于共享的数据格式正在彻底改变神经成像。我们将开发 软件来填补这两种趋势所造成的空白。我们将开发和完善软件, 来自大脑计划的数据。我们团队的可视化工具和dcm 2niix转换工具是核心工具 为我们的社区。我们最新一代的NiiVue将我们的工具带到了云端。NiiVue采用创新的 可视化技术,以显示体素,网格,流线和连接体格式常见于我们的领域。 NiiVue能够在任何设备上工作-电脑,手机或平板电脑,并能够利用现代高分辨率 显示器、高级显卡功能以及触摸和鼠标输入。我们将开发包装器, 我们的模块化NiiVue软件,以解决我们的领域的差距。首先,我们将扩展现有的ezBIDS, 共享数据的创建,以改善意图预测,使污损更鲁棒,提供视觉 确认自动化步骤,并轻松将匿名数据传输到公共存储库。二是我们 afNiiVue桌面工具将提供与AFNI数值工具交互的现代界面。三是我们 基于云的niiCloud网页将帮助科学家配置图像处理和分析, 检查结果。最后,基于jupyter notebook的ipyNiiVue将提供最先进的可视化, 科学家使用Python
英文摘要
Project Summary/Abstract Cloud-based analyses and easily shared data formats are revolutionizing neuroimaging. We will develop software to fill gaps created by these two trends. We will develop and refine software to visualize and analyze the data from the BRAIN Initiative. Our team’s visualization tools and dcm2niix conversion tools are core tools for our community. Our latest generation NiiVue brings our tools to the cloud. NiiVue uses innovative visualization techniques to display the voxel, mesh, streamline and connectome formats common in our field. NiiVue is able to work on any device – computer, phone or tablet and is able to exploit modern high-resolution displays, advanced graphics card capabilities as well as touch and mouse input. We will develop wrappers for our modular NiiVue software to address gaps in our field. First, we will extend our existing ezBIDS which eases the creation of shared data to improve intention prediction, make defacing more robust, provide visual confirmation for automated steps and ease transfer of anonymized data to public repositories. Second, our afNiiVue desktop tool will provide a modern interface for interacting with the AFNI numerical tools. Third, our cloud-based niiCloud web pages will aid scientists in configuring image processing and analyses as well as inspecting the results. Finally, the jupyter notebook based ipyNiiVue will provide state of the art visualization for scientists using Python.
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会议论文
Neuroimaging Core
Neuroimaging Core
Neuroimaging Core
Dissociating Components of the Attentional Network in Neglect
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