Slicer+PLUS: Collaborative, open-source software for ultrasound analysis
Slicer PLUS:用于超声分析的协作开源软件
基本信息
- 批准号:9535994
- 负责人:
- 金额:$ 54.44万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2016
- 资助国家:美国
- 起止时间:2016-09-21 至 2020-07-31
- 项目状态:已结题
- 来源:
- 关键词:AbdomenAccidentsAddressAlgorithmsAnatomyBloodChildClassificationClinicalCommunitiesComputer softwareDataData AnalysesDetectionDevelopmentDevicesDiagnosisDocumentationEmergency medical serviceEnvironmentFoundationsFrequenciesFutureGeneral PractitionersGoalsHemorrhageHome environmentHospitalsHuman ResourcesImageImageryInterventionIntra-abdominalLabelLettersLibrariesLifeMachine LearningMagnetismManufacturer NameMeasuresMedical DeviceMedical ImagingMethodsModalityMonitorOpticsOutputPatient TriagePatientsProcessProtocols documentationPublicationsPublishingResearchResearch PersonnelResearch SupportShapesSourceSpectrum AnalysisStethoscopesSystemTechnologyTestingTextureThree-dimensional analysisTimeTissuesTranslational ResearchTraumaUltrasonographyUnited States National Institutes of HealthVertebral columnWorkaging populationbasecatalystclinical translationcohesioncostdata acquisitionelastographyemergency service responderhospital patient careimage guided therapyimaging Segmentationinnovationinnovative technologieslearning strategynovelopen sourcephotoacoustic imagingpoint of careportabilityproduct developmentreconstructionresearch and developmentscoliosissignal processingsoftware developmenttransmission process
项目摘要
Abstract
The target users of the proposed Slicer+PLUS framework are researchers and developers who are focusing on
low-cost point-of-care ultrasound (POCUS) applications. POCUS applications are characterized by utilizing
low-cost, portable U/S systems; in the hands of novice operators; with novel data acquisition, signal
processing, and machine learning methods; with imprecise trackers; and in highly unconstrained point-of-care
environments, e.g.: at the scene of accidents for patient triage, in the offices of general practitioners for
scoliosis detection and monitoring, in patients' homes for an aging population, as well as throughout hospitals.
In these contexts, many are considering POCUS devices to be the stethoscopes of the future.
The foundation of Slicer+PLUS is the integration and extension of 3D Slicer, PLUS, and MUSiiC. We are
the developers of these libraries. We, and the users of our libraries, are proposing Slicer+PLUS so that the
Slicer, PLUS, and MUSiiC communities can come together and cohesively address the important challenges
and opportunities posed by POCUS applications. Over 30 letters of support are included with this application.
3D Slicer is a world-class, freely available open-source platform for medical image segmentation,
registration, and visualization. PLUS is a world-class, open-source library for communicating with ultrasound
machines and trackers (for following objects in 3D using magnetic, optical, and other technologies). MUSiiC is
a (previously closed source) library that focuses on advanced ultrasound acquisition and analysis methods,
such as ultrasound reconstruction pipelines, elastography, and photoacoustic imaging. Together, these toolkits
have averaged over 5,100 downloads per month for the past year.
A central tenant of our work is that POCUS applications should not be viewed as simply involving the use
of inexpensive, portable U/S systems; POCUS must be viewed as a new modality for it to attain its full
potential. POCUS must involve innovative, automated data analysis methods and workflows that can guide a
user to properly place and manipulate an ultrasound probe and interpret the returned ultrasound data. In
particular, the output of those workflows and analyses should be quantitative measures, not b-mode images,
since the expertise to interpret such images will not be readily available at points-of-care. To that end, the
proposed work goes well beyond simple integration of Slicer, PLUS, and MUSiiC. Multiple innovations are
proposed such as Ultrasound Spectroscopy for tissue labeling, Dynamic Textures for anatomic localization of
ultrasound probes, and self-tracking ultrasound probes.
To assess our progress towards our goals, our team includes our target users: researchers, medical device
manufacturers, and clinical innovators dedicated to low-cost POCUS applications. They will be validating our
efforts by integrating them into their research and translational POCUS product development projects.
摘要
Slicer+PLUS框架的目标用户是研究人员和开发人员,他们专注于
低成本的床旁超声(POCUS)应用。POCUS应用程序的特点是利用
低成本,便携式U/S系统;在新手操作员手中;具有新颖的数据采集,信号
处理和机器学习方法;使用不精确的跟踪器;以及在高度不受约束的即时护理中
环境,例如:在事故现场为病人分诊,在全科医生的办公室,
脊柱侧凸检测和监测,在老年人的家中,以及整个医院。
在这些背景下,许多人认为POCUS设备是未来的听诊器。
Slicer+PLUS的基础是3D Slicer、PLUS和MUSiiC的集成和扩展。我们
这些库的开发者。我们和我们图书馆的用户建议使用Slicer+PLUS,
Slicer、PLUS和MUSiiC社区可以团结起来,共同应对重要挑战
POCUS应用带来的机遇。超过30封支持信包含在此应用程序中。
3D Slicer是一个世界级的免费开源医学图像分割平台,
配准和可视化。PLUS是一个世界级的开源库,用于与超声进行通信
机器和跟踪器(用于使用磁性、光学和其他技术跟踪3D对象)。MUSiiC是
一个(以前封闭的源代码)库,专注于先进的超声采集和分析方法,
例如超声重建管线、弹性成像和光声成像。这些工具包合在一起
在过去一年里,平均每月下载量超过5,100次。
我们工作的一个中心租户是POCUS应用程序不应被视为简单地涉及使用
廉价的便携式U/S系统; POCUS必须被视为一种新的模式,以实现其全面的
潜力POCUS必须涉及创新的自动化数据分析方法和工作流程,
用户正确放置和操作超声探头并解释返回的超声数据。在
特别是,这些工作流程和分析的输出应该是定量测量,而不是B模式图像,
因为解释这种图像的专业知识在护理点不容易获得。为此,
拟议的工作远远超出了Slicer、PLUS和MUSiiC的简单集成。多项创新是
提出了诸如用于组织标记的超声光谱,用于解剖定位的动态纹理,
超声探头和自跟踪超声探头。
为了评估我们实现目标的进展情况,我们的团队包括我们的目标用户:研究人员,医疗器械
制造商和致力于低成本POCUS应用的临床创新者。他们将验证我们的
通过将其整合到他们的研究和翻译POCUS产品开发项目的努力。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
STEPHEN R AYLWARD其他文献
STEPHEN R AYLWARD的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('STEPHEN R AYLWARD', 18)}}的其他基金
Slicer+PLUS: Collaborative, open-source software for ultrasound analysis
Slicer PLUS:用于超声分析的协作开源软件
- 批准号:
9750736 - 财政年份:2016
- 资助金额:
$ 54.44万 - 项目类别:
Automated Assessment of Leptomeningeal Collaterals on CT Angiograms
CT 血管造影上软脑膜循环的自动评估
- 批准号:
8905209 - 财政年份:2015
- 资助金额:
$ 54.44万 - 项目类别:
Automated Assessment of Leptomeningeal Collaterals on CT Angiograms
CT 血管造影上软脑膜循环的自动评估
- 批准号:
9622038 - 财政年份:2015
- 资助金额:
$ 54.44万 - 项目类别:
Multimodality image-based assessment system for traumatic brain injury
基于图像的多模态脑外伤评估系统
- 批准号:
8601141 - 财政年份:2013
- 资助金额:
$ 54.44万 - 项目类别:
Accelerating Community-Driven Medical Innovation with VTK
借助 VTK 加速社区驱动的医疗创新
- 批准号:
8652452 - 财政年份:2013
- 资助金额:
$ 54.44万 - 项目类别:
Accelerating Community-Driven Medical Innovation with VTK
借助 VTK 加速社区驱动的医疗创新
- 批准号:
10091434 - 财政年份:2013
- 资助金额:
$ 54.44万 - 项目类别:
In-field FAST Procedure Support and Automation
现场 FAST 程序支持和自动化
- 批准号:
8472102 - 财政年份:2013
- 资助金额:
$ 54.44万 - 项目类别:
Multimodality image-based assessment system for traumatic brain injury
基于图像的多模态脑外伤评估系统
- 批准号:
8453963 - 财政年份:2013
- 资助金额:
$ 54.44万 - 项目类别:
Accelerating Community-Driven Medical Innovation with VTK
借助 VTK 加速社区驱动的医疗创新
- 批准号:
9910382 - 财政年份:2013
- 资助金额:
$ 54.44万 - 项目类别:
Accelerating Community-Driven Medical Innovation with VTK
借助 VTK 加速社区驱动的医疗创新
- 批准号:
8505967 - 财政年份:2013
- 资助金额:
$ 54.44万 - 项目类别:
相似海外基金
Factors and effect of visual inattention on fall accidents
视觉注意力不集中对坠落事故的影响因素及影响
- 批准号:
23K19000 - 财政年份:2023
- 资助金额:
$ 54.44万 - 项目类别:
Grant-in-Aid for Research Activity Start-up
SBIR Phase I: Comprehensive, Human-Centered, Safety System Using Physiological and Behavioral Sensing to Predict and Prevent Workplace Accidents
SBIR 第一阶段:利用生理和行为感知来预测和预防工作场所事故的综合性、以人为本的安全系统
- 批准号:
2321538 - 财政年份:2023
- 资助金额:
$ 54.44万 - 项目类别:
Standard Grant
Preventing Accidents in School lunch for Food Allergies: Consideration of Strategies and Development of Support Applications.
预防学校午餐中的食物过敏事故:考虑策略和开发支持应用程序。
- 批准号:
23K01977 - 财政年份:2023
- 资助金额:
$ 54.44万 - 项目类别:
Grant-in-Aid for Scientific Research (C)
Political Geographies of Human Accidents and Trauma Care in Mumbai's Commuter Railways
孟买通勤铁路中人类事故和创伤护理的政治地理
- 批准号:
ES/X006239/1 - 财政年份:2022
- 资助金额:
$ 54.44万 - 项目类别:
Fellowship
Multiscale, Multi-fidelity and Multiphysics Bayesian Neural Network (BNN) Machine Learning (ML) Surrogate Models for Modelling Design Based Accidents
用于基于事故建模设计的多尺度、多保真度和多物理场贝叶斯神经网络 (BNN) 机器学习 (ML) 替代模型
- 批准号:
2764855 - 财政年份:2022
- 资助金额:
$ 54.44万 - 项目类别:
Studentship
OTIMO - Applying telematics to the learner driver market through innovations in AI and behavioural intervention, to improve driving and reduce accidents.
OTIMO - 通过人工智能和行为干预创新,将远程信息处理应用于学习驾驶员市场,以改善驾驶并减少事故。
- 批准号:
10035763 - 财政年份:2022
- 资助金额:
$ 54.44万 - 项目类别:
Collaborative R&D
Comprehensive safety strategy to achieve reducing accidents of central venous access port catheter rapture
综合安全策略,实现减少中心静脉通路导管断裂事故
- 批准号:
22K17330 - 财政年份:2022
- 资助金额:
$ 54.44万 - 项目类别:
Grant-in-Aid for Early-Career Scientists
Practical application of exposure dose evaluation method by DNA damage analysis for radiation exposure accidents
DNA损伤分析照射剂量评估方法在辐射事故中的实际应用
- 批准号:
21H01861 - 财政年份:2021
- 资助金额:
$ 54.44万 - 项目类别:
Grant-in-Aid for Scientific Research (B)
Computational Scientific Study on Mechanism of Multiphase Thermal-Hydraulic Phenomena Related to IVR in Core Disruptive Accidents
堆芯破坏性事故中与IVR相关的多相热工水力现象机理的计算科学研究
- 批准号:
21K04944 - 财政年份:2021
- 资助金额:
$ 54.44万 - 项目类别:
Grant-in-Aid for Scientific Research (C)
Crutch Walk Training with AR Presentation of Near Miss Accidents by Disturbances in Living Space
拐杖行走训练与 AR 展示生活空间干扰造成的未遂事故
- 批准号:
21K12816 - 财政年份:2021
- 资助金额:
$ 54.44万 - 项目类别:
Grant-in-Aid for Scientific Research (C)














{{item.name}}会员




