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SBIR Phase II: A Non-invasive Image-based Skeletal Muscle Analytics Tool

SBIR Phase II: A Non-invasive Image-based Skeletal Muscle Analytics Tool
SBIR II 期:基于图像的非侵入性骨骼肌分析工具
批准号:
1556135
负责人:
Xue Feng
金额:
$74.76万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-03-15 至 2019-08-31
关键词:

项目摘要

项目成果

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中文摘要
翻译
这个小企业创新研究(SBIR)第二阶段项目的更广泛的影响/商业潜力是提供一个新的工具,揭示有关骨骼肌力量和健康的重要信息。肌肉无力是我们社会中普遍存在的问题,包括关节疾病患者,老年人,肥胖患者和神经肌肉疾病患者。所有这些问题都以不同且非直观的方式影响全身的肌肉;然而,迄今为止,还没有允许在逐肌肉的基础上定量测量肌肉大小并进行特定分析以解决肌肉无力问题的市场化技术。由于目前的高成本,最初的目标客户将是精英运动员组织,目标是使用该技术来提高性能,并提供更多的量化指标来预测受伤的易感性和做出重返运动的决定。然而,随着研究和开发,以降低成本,最终目标是使一个广泛使用的临床工具,预防,诊断和治疗与肌肉骨骼疾病和流动性有关的健康状况,这将产生广泛的社会影响。拟议的项目将提供一个重大的进步,在基于图像的建模和数据分析工具,以允许高通量成像,快速准确的肌肉分割和高效的数据分析。目前,物理治疗师,运动教练和力量和空调教练只有非常钝的工具来评估每个人?的力量和非常有限的信息有关的最佳肌肉轮廓。因此,训练和康复方法是通过经验和试错来开发的。这里提出的技术通过使用图像到模型管道来量化肌肉大小并基于量化提供有价值的和可操作的信息来解决这些问题。然而,广泛采用该技术的障碍包括特定的磁共振成像(MRI)协议和冗长的图像分割过程。在上一个供资周期,这两个问题已通过重大技术进步得到解决。本供资周期的拟议活动将继续技术开发进程,以通过改进图像分割进程进一步降低成本,并通过先进的数据分析提供额外价值。它最终将成为改善肌肉健康的革命性工具。
英文摘要
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to provide a new tool revealing important information regarding skeletal muscle strength and health. Muscle weakness is a pervasive problem across our society, including people with joint disease, aging people, obese people, and people with neuromuscular disorders. All of these problems affect muscles across the body in different and non-intuitive ways; however, to date there has not been marketed technology that allows for quantitative measurement of muscle size on a muscle-by-muscle basis and specific analysis to address the muscle weakness problem. Due to the current high cost, the initial targeted customers will be elite athlete organizations, with the goal of using the technology to improve performance as well as to provide more quantitative metrics for predicting injury susceptibility and make return-to-sport decisions. However, with research and development to bring down the cost, the ultimate goal is to make a broadly used clinical tool for prevention, diagnosis, and treatment of health conditions related to musculoskeletal disease and mobility, which will have broad societal impact.The proposed project will provide a major advancement in image-based modeling and data analysis tools in order to allow high-throughput imaging, rapid and accurate segmentation of muscles and efficient data analysis. Currently, physical therapists, athletic trainers and strength and conditioning coaches only have very blunt tools to assess each individual?s strength and very limited information about the optimal muscle profile. Therefore, training and rehabilitative approaches are developed via experience and trial and error. The technology proposed here solves these problems by making using of an image-to-model pipeline to quantify muscle size and provide valuable and actionable information based on the quantification. However, the obstacles for a wide adoption of this technology include specific magnetic resonance imaging (MRI) protocols and lengthy image segmentation process. In the previous funding cycle these two problems have been addressed with substantial technology advancements. The proposed activities in this funding cycle will continue the technical development process to further bring down the cost with improved image segmentation process and provide additional value with advanced data analysis. It will ultimately be a revolutionary tool to improve muscle health.
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