BIGDATA Small Project Structurization and Direct Search of Medical Image Data
BIGDATA小项目结构化和医学图像数据直接搜索
基本信息
- 批准号:8599843
- 负责人:
- 金额:$ 22.49万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2013
- 资助国家:美国
- 起止时间:2013-06-01 至 2016-05-31
- 项目状态:已结题
- 来源:
- 关键词:ArchivesBrainClinicalCommunitiesDataDatabasesDecision MakingDiagnosisEducationEvidence Based MedicineGrantHealth Services ResearchImageInformation SystemsMagnetic Resonance ImagingMedicalMedical ImagingMedical RecordsNatural Language ProcessingPatientsPhenotypePhysiciansProtocols documentationReportingResolutionScanningSliceStructureTechnologyTestingTextbeneficiaryclinical decision-makingevidence baseexperienceimprovedoutcome forecastprototyperadiologist
项目摘要
DESCRIPTION (provided by applicant): IBM estimates that 30% of the entire data in the world is medical information. Medical images occupy a significant portion of medical records with approximately 100 million scans in US and growing every year. In addition, the data size from each scan steadfastly increases as the image resolution improves. These BigData are not structured and due to lack of standardized imaging protocols, they are highly heterogeneous with different spatial resolutions, contrasts, slice orientations, etc. In this project, we will deelop a technology to structure and search medical imaging information, which will make the past data available for education and evidence-based clinical decision-making. In this grant, we will focus on brain MRI, which comprises the largest portion of MRI data. The target community will be physicians who make decisions and the patients will be the ultimate beneficiaries. Currently, radiological image data are stored in clinical database called PACS. The image data in PACS are not structured. Consequently, once the diagnosis of a patient is completed, most of the data in PACS are currently discarded in the archive. Radiologists rely on their experience and education to reach medical decisions. This is a typical problem in medical practice that calls for objective evidence-based medicine. There are many ongoing attempts to structure the text fields of PACS, which include natural language processing of free-text radiological reports, clinical information, and diagnosis. In our approach, we propose to structure the image data, not text fields, to support direct search of images. Namely, physicians will submit an image of a new patient and search past images with similar anatomical phenotypes. Then, the clinical reports of the retrieved data will be compiled for a statistical report of the diagnosis and prognosis. We believe this image structuration is the key to "unlock the vast amounts of information currently stored" in PACS and use them for education and modern evidence-based medical decisions. The specific aims are; Objective 1: To develop and test the accuracy of high-throughput image structuration technologies Objective 2: To develop and test the image search engine Objective 3: Capacity Building Requirement: To develop prototype cloud system for data structuration / search services for research and educational purposes
描述(由申请人提供):IBM估计全世界30%的数据是医疗信息。在美国,医学图像占据了医疗记录的很大一部分,大约有1亿次扫描,并且每年都在增长。此外,每次扫描的数据大小随着图像分辨率的提高而稳步增加。这些大数据是非结构化的,由于缺乏标准化的成像协议,它们具有高度的异质性,具有不同的空间分辨率、对比度、切片方向等。在这个项目中,我们将开发一种结构化和搜索医学影像信息的技术,这将使过去的数据可用于教育和循证临床决策。在本次资助中,我们将重点关注脑MRI,这是MRI数据中最大的一部分。目标群体将是做决定的医生,而患者将是最终的受益者。目前,影像学数据存储在临床数据库PACS中。PACS中的图像数据是非结构化的。因此,一旦完成对患者的诊断,PACS中的大部分数据目前都被丢弃在存档中。放射科医生依靠他们的经验和教育来做出医疗决定。这是医学实践中的典型问题,需要客观的循证医学。有许多正在进行的尝试来构建PACS的文本字段,其中包括对自由文本放射报告、临床信息和诊断的自然语言处理。在我们的方法中,我们建议结构化图像数据,而不是文本字段,以支持直接搜索图像。也就是说,医生将提交新患者的图像并搜索具有相似解剖表型的过去图像。然后,将检索数据的临床报告汇编为诊断和预后的统计报告。我们相信这种图像结构是“解锁目前存储在PACS中的大量信息”并将其用于教育和现代循证医疗决策的关键。具体目标是;目标1:开发和测试高通量图像结构化技术的准确性目标2:开发和测试图像搜索引擎目标3:能力建设需求:开发用于研究和教育目的的数据结构化/搜索服务的原型云系统
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(1)
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 }}
MICHAEL I MILLER其他文献
MICHAEL I MILLER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('MICHAEL I MILLER', 18)}}的其他基金
Tracing Spread of Pathology Within The HD Brain via Automated Neuroimaging
通过自动神经影像追踪 HD 大脑内病理学的传播
- 批准号:
10155594 - 财政年份:2018
- 资助金额:
$ 22.49万 - 项目类别:
Tracing Spread of Pathology Within The HD Brain via Automated Neuroimaging
通过自动神经影像追踪 HD 大脑内病理学的传播
- 批准号:
9924675 - 财政年份:2018
- 资助金额:
$ 22.49万 - 项目类别:
Neurodegenerative and Neurodevelopmental Subcortical Shape Diffeomorphometry
神经退行性和神经发育皮层下形状微形态测量
- 批准号:
9769057 - 财政年份:2016
- 资助金额:
$ 22.49万 - 项目类别:
Neurodegenerative and Neurodevelopmental Subcortical Shape Diffeomorphometry
神经退行性和神经发育皮层下形状微形态测量
- 批准号:
9355187 - 财政年份:2016
- 资助金额:
$ 22.49万 - 项目类别:
Continued Development and Maintenance of MriStudio
MriStudio的持续开发和维护
- 批准号:
9896853 - 财政年份:2013
- 资助金额:
$ 22.49万 - 项目类别:
Continued Development and Maintenance of MriStudio
MriStudio的持续开发和维护
- 批准号:
8610697 - 财政年份:2013
- 资助金额:
$ 22.49万 - 项目类别:
Continued Development and Maintenance of MriStudio
MriStudio的持续开发和维护
- 批准号:
9118340 - 财政年份:2013
- 资助金额:
$ 22.49万 - 项目类别:
Continued Development and Maintenance of MriStudio
MriStudio的持续开发和维护
- 批准号:
10159312 - 财政年份:2013
- 资助金额:
$ 22.49万 - 项目类别:
BIGDATA Small Project Structurization and Direct Search of Medical Image Data
BIGDATA小项目结构化和医学图像数据直接搜索
- 批准号:
8852613 - 财政年份:2013
- 资助金额:
$ 22.49万 - 项目类别:
相似国自然基金
Sitagliptin通过microbiota-gut-brain轴在2型糖尿病致阿尔茨海默样变中的脑保护作用机制
- 批准号:81801389
- 批准年份:2018
- 资助金额:21.0 万元
- 项目类别:青年科学基金项目
平扫描数据导引的超低剂量Brain-PCT成像新方法研究
- 批准号:81101046
- 批准年份:2011
- 资助金额:23.0 万元
- 项目类别:青年科学基金项目
相似海外基金
Quantum-Enabled Brain Imaging: A Pathway to Clinical Utility
量子脑成像:临床应用的途径
- 批准号:
10107115 - 财政年份:2024
- 资助金额:
$ 22.49万 - 项目类别:
Small Business Research Initiative
Metrics for Brain Controlled Communication: A comprehensive review of clinical outcome assessments for communication brain computer interfaces in amyotrophic lateral sclerosis
脑控制通信指标:肌萎缩侧索硬化症通信脑机接口临床结果评估的全面综述
- 批准号:
10848139 - 财政年份:2023
- 资助金额:
$ 22.49万 - 项目类别:
Acquisition-independent machine learning for morphometric analysis of underrepresented aging populations with clinical and low-field brain MRI
独立于采集的机器学习,通过临床和低场脑 MRI 对代表性不足的老龄化人群进行形态计量分析
- 批准号:
10739049 - 财政年份:2023
- 资助金额:
$ 22.49万 - 项目类别:
Transforming Research And Clinical Knowledge in Geriatric Traumatic Brain Injury (TRACK-GERI)
转变老年创伤性脑损伤的研究和临床知识 (TRACK-GERI)
- 批准号:
10741270 - 财政年份:2023
- 资助金额:
$ 22.49万 - 项目类别:
Technology platform for clinical application of multi-targeted neutron capture therapy for brain tumors
脑肿瘤多靶点中子俘获治疗临床应用技术平台
- 批准号:
23H03024 - 财政年份:2023
- 资助金额:
$ 22.49万 - 项目类别:
Grant-in-Aid for Scientific Research (B)
Long-term outcomes of traumatic brain injury in veterans: a clinical, neuropsychological, and neuropathological study
退伍军人创伤性脑损伤的长期结果:临床、神经心理学和神经病理学研究
- 批准号:
MR/Y001850/1 - 财政年份:2023
- 资助金额:
$ 22.49万 - 项目类别:
Fellowship
Transforming Research And Clinical Knowledge in Geriatric Traumatic Brain Injury (TRACK-GERI)
转变老年创伤性脑损伤的研究和临床知识 (TRACK-GERI)
- 批准号:
10738972 - 财政年份:2023
- 资助金额:
$ 22.49万 - 项目类别:
Mapping functional brain connectivity, neurodevelopment, and imaging-genetic associations in individuals with genetic and clinical risk factors for neuropsychiatric illness
绘制具有神经精神疾病遗传和临床危险因素的个体的功能性大脑连接、神经发育和成像-遗传关联
- 批准号:
10678553 - 财政年份:2023
- 资助金额:
$ 22.49万 - 项目类别:
Brain-based and clinical phenotyping of pain pharmacotherapy in knee OA
膝关节 OA 疼痛药物治疗的脑基和临床表型
- 批准号:
10735060 - 财政年份:2023
- 资助金额:
$ 22.49万 - 项目类别:
Enhancing clinical brain MRI scans with deep learning for improved deep brain stimulation
通过深度学习增强临床脑 MRI 扫描,以改善深部脑刺激
- 批准号:
2897458 - 财政年份:2023
- 资助金额:
$ 22.49万 - 项目类别:
Studentship