Inference and Model Building for Vision-based Estimation of Transmissive Objects
Inference and Model Building for Vision-based Estimation of Transmissive Objects
批准号:
RGPIN-2017-05638
负责人:
Brubaker, Marcus
金额:
$2.84万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2018
资助国家:
加拿大
项目状态:
已结题
起止时间:
2018-01-01 至 2019-12-31
中文摘要
这项建议旨在促进计算机视觉和图像处理领域的最新水平,目的是扩大和加强成像模式在我们对世界的理解中的使用。图像是一个丰富的信息来源,在许多情况下都很容易捕捉到。处理这些图像并从中提取含义的能力是计算机视觉的关键目标。这项建议的长期目标和PI的研究计划总体上是理论和实践发展的模型,使之能够从图像估计世界的属性。一个这样的问题是对透射物的详细3D结构的估计。这类物体的成像和重建涉及一系列领域,包括:云、玻璃、水或烟等半透明物体的光学成像,用于医疗目的的人和动物的X射线成像,以及透射式电子成像或材料和生物标本。*本提议的目标集中在透射式电子成像,目的是建立电子冷冻显微镜(Cryo-EM)的新方法。讨论了与从低温电子显微镜图像估计生物分子(如蛋白质和病毒)的3D结构有关的具体问题。低温电子显微镜是一种快速发展起来的测定生物分子实验结构的方法。DNA的功能有时被类比为生命的源码。继续这个类比,蛋白质和病毒是编译后的程序,它们采取分子机器的形式,在细胞水平上“执行生命”。确定这些机器的3D结构并了解它们的工作原理不仅具有基本的科学意义,而且对于了解疾病以及开发新药和治疗方法也是至关重要的。这里提出的研究将推进最先进的技术,并对低温EM产生重大影响,从而对加拿大和世界各地的科学和医学的许多方面产生重大影响。通过提高估计结构的可靠性和分辨率,本文提出的方法将形成快速结构确定方法的基础,该方法可用于更快地开发不太可能产生意外副作用的新药。它们还将使科学家能够研究细胞中前所未见的机制,因为这些分子机器的运动可以直接捕获。
英文摘要
This proposal seeks to further the state of the art in the field of computer vision and image processing, with the goal of expanding and reinforcing the use of imaging modalities in our understanding of the world. Images are a rich source of information which are readily captured in many scenarios. The ability to process these images and extract meaning from them is the key goal of computer vision. The long-term objective of this proposal and the PI's research program in general is the theoretical and practical development of models which enable the estimation of properties of the world from images. One such problem is the estimation of detailed 3D structure of transmissive objects. Imaging and reconstruction of such objects arises in a range of domains including: optical imaging of translucent objects like clouds, glass, water or smoke, x-ray imaging of humans and animals for medical purposes, and transmission electron imaging or materials and biological specimens.******The objectives of this proposal focus on transmission electron imaging with the aim to build new methods for electron cryomicroscopy (cryo-EM). Specific problems relating to the estimation of the 3D structure of biological molecules such as proteins and viruses from cryo-EM images are considered. Cryo-EM is a rapidly emerging method for experimental structure determination of biological molecules. The function of DNA has sometimes been explained by analogy as the source code of life. Continuing this analogy, proteins and viruses are the compiled programs which take the form of molecular machines that “execute life” at a cellular level. Determining the 3D structures of these machines and understanding how they work is not only of fundamental scientific interest, it is also critical in the understanding of disease and the development of novel drugs and treatments.******The research proposed here would advance the state-of-the-art and have significant impacts on cryo-EM and consequently on many aspects of science and medicine both within Canada and around the world. By improving the reliability and resolution of estimation structures, the methods proposed here would form the basis for rapid structure determination methods which could be used to more quickly develop new drugs which would be less likely to have unexpected side-effects. They would also allow scientists to study never before seen mechanisms in the cell as the motion of these molecular machines could be captured directly.**
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Inference and Model Building for Vision-based Estimation of Transmissive Objects
-
批准号:RGPIN-2017-05638
-
项目类别:Discovery Grants Program - Individual
-
资助金额:$2.84万
-
财政年份:2022
-
负责人:Brubaker, Marcus
-
依托单位:
Inference and Model Building for Vision-based Estimation of Transmissive Objects
-
批准号:RGPIN-2017-05638
-
项目类别:Discovery Grants Program - Individual
-
资助金额:$2.84万
-
财政年份:2021
-
负责人:Brubaker, Marcus
-
依托单位:
Inference and Model Building for Vision-based Estimation of Transmissive Objects
-
批准号:RGPIN-2017-05638
-
项目类别:Discovery Grants Program - Individual
-
资助金额:$2.84万
-
财政年份:2019
-
负责人:Brubaker, Marcus
-
依托单位:
Inference and Model Building for Vision-based Estimation of Transmissive Objects
-
批准号:RGPIN-2017-05638
-
项目类别:Discovery Grants Program - Individual
-
资助金额:$2.84万
-
财政年份:2017
-
负责人:Brubaker, Marcus
-
依托单位:
国内基金
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