Reconstruction algorithms for time-domain diffuse optical tomography imaging of small animals

小动物时域漫射光学断层成像重建算法

基本信息

  • 批准号:
    RGPIN-2015-05926
  • 负责人:
  • 金额:
    $ 1.82万
  • 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
  • 起止时间:
    2018-01-01 至 2019-12-31
  • 项目状态:
    已结题

项目摘要

This proposal is about the development of efficient computer programs (so-called algorithms) to obtain images in 3D of the interior of small laboratory animals (mice) used in biomedical research. The technique considered here for obtaining these images is diffuse optical tomography (DOT), a non-invasive medical imaging modality whereby non-ionizing light from a laser is used to illuminate an animal at several points on its skin. The light exiting the animal after its propagation through its body is measured (detected) at several positions again on its skin. The task of algorithms is to obtain from such surface measurements data a 3D image of the interior of the animal. For DOT, this is a difficult mathematical problem whose solution may take up to several hours on modern desktop computers before an image is obtained. Furthermore, a particularity of our work is that we resort to a detection technique, so-called time-domain optical measurements, that provides for information richer data. This has the potential of improving the spatial resolution of the images obtained and making them more quantitative, but since more data must be handled with such measurements, the computing time is further increased. Exploiting such data prompts for efficient numerical techniques to reduce the computational power needed by our algorithms. This proposal is about the development of such techniques that should lead to a decrease in computing times by an estimated factor of 10 to 100. This research is important because 3D pre-clinical imaging of small animals is a key tool in biomedical research that allows studying fundamental processes involved in disease development (cancer) and treatment (drug design, therapy assessment). This ultimately has impacts on the quality of treatments that can be offered to diseased patients, thus improving their quality of life and prognostics. The research program proposed here will provide end-users of DOT with faster feedback on their protocols which is important in their daily duties. Notably, optical imaging as developed here, allows studying processes that cannot be visualized with other medical imaging modalities, thus complementing these other modalities. The proposal will allow training 4 doctoral degree students along with initiating 5 bachelor's degree students to research.
该提案是关于开发高效的计算机程序(所谓的算法),以获得用于生物医学研究的小型实验动物(小鼠)内部的3D图像。这里考虑的获得这些图像的技术是漫射光学断层扫描(DOT),这是一种非侵入性医学成像方式,利用激光发出的非电离光照射动物皮肤上的几个点。光通过动物的身体传播后,在其皮肤的几个位置再次测量(检测)出光。算法的任务是从这些表面测量数据中获得动物内部的3D图像。对于DOT来说,这是一个困难的数学问题,在现代台式计算机上解决它可能需要几个小时才能获得图像。此外,我们工作的一个特点是我们采用了一种检测技术,即所谓的时域光学测量,它提供了信息更丰富的数据。这有可能提高所获得图像的空间分辨率,使它们更加定量,但由于必须处理更多的数据,因此计算时间进一步增加。利用这样的数据提示有效的数值技术,以减少我们的算法所需的计算能力。这个建议是关于这样的技术的发展,它将导致计算时间减少大约10到100倍。这项研究很重要,因为小动物的3D临床前成像是生物医学研究的关键工具,可以研究涉及疾病发展(癌症)和治疗(药物设计,治疗评估)的基本过程。这最终会影响到可以提供给患病患者的治疗质量,从而改善他们的生活质量和预后。这里提出的研究计划将为DOT的最终用户提供对其协议的更快反馈,这在他们的日常工作中很重要。值得注意的是,这里发展的光学成像,可以研究其他医学成像模式无法可视化的过程,从而补充了这些其他模式。该提案将允许培养4名博士学位学生,同时启动5名学士学位学生进行研究。

项目成果

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BérubéLauzière, Yves其他文献

BérubéLauzière, Yves的其他文献

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{{ truncateString('BérubéLauzière, Yves', 18)}}的其他基金

Radiation propagation modelling and image reconstruction for X-ray time-of-flight computed tomography
X 射线飞行时间计算机断层扫描的辐射传播建模和图像重建
  • 批准号:
    RGPIN-2021-03858
  • 财政年份:
    2022
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
Radiation propagation modelling and image reconstruction for X-ray time-of-flight computed tomography
X 射线飞行时间计算机断层扫描的辐射传播建模和图像重建
  • 批准号:
    RGPAS-2021-00039
  • 财政年份:
    2022
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Accelerator Supplements
Radiation propagation modelling and image reconstruction for X-ray time-of-flight computed tomography
X 射线飞行时间计算机断层扫描的辐射传播建模和图像重建
  • 批准号:
    RGPIN-2021-03858
  • 财政年份:
    2021
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
Radiation propagation modelling and image reconstruction for X-ray time-of-flight computed tomography
X 射线飞行时间计算机断层扫描的辐射传播建模和图像重建
  • 批准号:
    RGPAS-2021-00039
  • 财政年份:
    2021
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Accelerator Supplements
QSciTech: Bridging the Gap between Quantum Science and Quantum Technologies - Training the Next Generation of Quantum Scientists, Engineers and Entrepreneurs
QSciTech:弥合量子科学和量子技术之间的差距 - 培训下一代量子科学家、工程师和企业家
  • 批准号:
    511602-2018
  • 财政年份:
    2021
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Collaborative Research and Training Experience
QSciTech: Bridging the Gap between Quantum Science and Quantum Technologies - Training the Next Generation of Quantum Scientists, Engineers and Entrepreneurs
QSciTech:弥合量子科学和量子技术之间的差距 - 培训下一代量子科学家、工程师和企业家
  • 批准号:
    511602-2018
  • 财政年份:
    2020
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Collaborative Research and Training Experience
QSciTech: Bridging the Gap between Quantum Science and Quantum Technologies - Training the Next Generation of Quantum Scientists, Engineers and Entrepreneurs
QSciTech:弥合量子科学和量子技术之间的差距 - 培训下一代量子科学家、工程师和企业家
  • 批准号:
    511602-2018
  • 财政年份:
    2019
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Collaborative Research and Training Experience
Reconstruction algorithms for time-domain diffuse optical tomography imaging of small animals
小动物时域漫射光学断层成像重建算法
  • 批准号:
    RGPIN-2015-05926
  • 财政年份:
    2019
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
QSciTech: Bridging the Gap between Quantum Science and Quantum Technologies - Training the Next Generation of Quantum Scientists, Engineers and Entrepreneurs
QSciTech:弥合量子科学和量子技术之间的差距 - 培训下一代量子科学家、工程师和企业家
  • 批准号:
    511602-2018
  • 财政年份:
    2018
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Collaborative Research and Training Experience
Reconstruction algorithms for time-domain diffuse optical tomography imaging of small animals
小动物时域漫射光学断层成像重建算法
  • 批准号:
    RGPIN-2015-05926
  • 财政年份:
    2017
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual

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