Stanford's Translational Biomedical Imaging Instrumentation (TBI2) Training Program
Stanford's Translational Biomedical Imaging Instrumentation (TBI2) Training Program
批准号:
10627475
负责人:
Kim Butts-Pauly
金额:
$10.92万
依托单位:
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:
2023-05-01 至 2028-04-30
中文摘要
摘要
这份提案概述了为我们的多学科博士前培训项目斯坦福大学的
转化型生物医学成像仪器(TBI2)培训计划。生物医学成像技术
继续以快速的速度发展。我们的使命是培养下一代研究人员和发明家
翻译生物医学影像仪器以满足国家对高技能科学家的需求
在这个领域。在国家一级,显然需要训练有素的生物医学成像研究人员。
填补学术界、工业界和政府职位的工具,以推动创新周期
这最终会影响人类健康。我们实现翻译影响力的愿景包括从板凳到
床边(临床翻译)和工作台到行业(翻译创业)。我们的愿景是有动力的
根据我们受训人员的职业兴趣,他们中的许多人在学术领域寻求专业机会,许多人
他们中的一些人寻求通过行业的方式将他们的技能转化为翻译影响。
斯坦福大学在以下领域提供高度创新和独特的多学科研究环境
生物医学成像仪器。TBI2教师在创新和创新方面有着出色的记录
横跨磁共振成像/光谱学、计算机断层扫描、超声波、正电子发射计算机断层扫描、
分子成像和光学成像。这些模式的培训,外加接触混合成像系统
(X光/MR、PET/MR和MR引导的聚焦超声),将为学员提供广泛的使用经验
先进的生物医学成像技术。由我们久负盛名的研究导师和临床合作伙伴
导师将提供机会,推动我们的成年人和
儿科医院环境。
平行机会将提供翻译创业方面的经验,以加快新产品的进入
将技术转化为产业,以产生全球影响。医学成像物理学的教学培训机会
系统、图像和信号处理、放射解剖学和生理学、高级诊断学、介入
程序,放射治疗提供了丰富的学习环境。此外,人工智能和
多年来,机器学习一直是推动斯坦福大学成像创新的关键技术,以及培训
在人工智能和机器学习方面形成了这一新培训计划的主要重点。它是
跨成像模式编织,包括上游和下游应用。
受训者还将获得严谨和可重复的实验设计方面的专业知识,以及
对他们的研究的思考。完成我们培训计划的学员将拥有一套独特的技能,
满足了国家对具有先进生物医学成像专业知识的研究人员和领导者的明显需求
仪器仪表。
英文摘要
ABSTRACT
This proposal outlines a request to fund our multidisciplinary predoctoral training program, Stanford’s
Translational Biomedical Imaging Instrumentation (TBI2) training program. Biomedical imaging technology
continues to evolve at a rapid pace. Our mission is to train the next generation of researchers and inventors in
translational biomedical imaging instrumentation in order to meet the national demand for highly skilled scientists
in this field. At the national level, there persists a clear need for trained researchers in biomedical imaging
instrumentation to fill positions in academia, industry, and government in order to fuel the cycles of innovation
that ultimately impact human health. Our vision for achieving translational impact includes both bench to
bedside (clinical translation) and bench to industry (translational entrepreneurship). Our vision is motivated
by the career interests of our trainees, many of whom seek professional opportunities in academics and many
of whom seek to translate their skills for translational impact by way of industry.
Stanford University provides a highly innovative and unique multidisciplinary research environment in
biomedical imaging instrumentation. The TBI2 faculty have an outstanding track record of innovation and
translation that spans magnetic resonance imaging/spectroscopy, computed tomography, ultrasound, PET,
molecular imaging, and optical imaging. Training in these modalities, plus exposure to hybrid imaging systems
(X-ray/MR, PET/MR, and MR-guided focused ultrasound), will provide trainees with broad experience using
advanced biomedical imaging technologies. Mentoring by our well-established research mentors and clinical co-
mentors will provide opportunities to push developments towards translational applications in our adult and
pediatric hospital settings.
Parallel opportunites will provide experience in translational entrepreneurship to accelerate the entry of new
technologies into industry for worldwide impact. Didactic training opportunities in the physics of medical imaging
systems, image and signal processing, radiologic anatomy and physiology, advanced diagnostics, interventional
procedures, and radiation therapy provide a rich learning environment. Furthermore, artificial intelligence and
machine learning have been key technologies driving imaging innovation at Stanford for many years, and training
in artificial intelligence and machine learning form a substantial emphasis of this new training program. It is
woven across imaging modalities and includes both upstream and downstream applications.
Trainees will also gain expertise in rigorous and reproducible experimental design, plus the ethical
considerations of their research. TBI2 trainees that complete our training program will have a unique skill set that
fullfills a distinct national need for researchers and leaders with expertise in advanced biomedical imaging
instrumentation.
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会议论文
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