Anatomically Embedded Representations for Medical Image Registration in Clinical Applications
临床应用中医学图像配准的解剖嵌入式表示
基本信息
- 批准号:222860-2012
- 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:2014
- 资助国家:加拿大
- 起止时间:2014-01-01 至 2015-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Medical image registration is an essential task in a variety of clinical applications such as diagnosis, follow-up of pathologies, treatment planning and simulation, intra-operative surgery assistance and treatment outcome assessment. Despite the tremendous progress already made by the research community and the huge number of sophisticated methods proposed for intra-modal and multimodal image registration, their applicability in clinical environments is still limited. The most important bottlenecks preventing a wide use of these methods in clinical applications are not only their precision and robustness but also their associated computational cost. The overall objective of our research program is to pursue fundamental and applied research for the development of novel representations of anatomical structures of the trunk and registration algorithms with high potential impact in non invasive diagnosis, clinical follow-up, surgical planning and assistance in the treatment of adolescent idiopathic scoliosis deformities. More specifically, we will instigate a new representation of the triangulated mesh surface of the trunk, obtained from non invasive 3D cameras, using spectral graph theory. The novelty of our approach will lie in using anatomical features of the trunk as weights in graph nodes and as extra embedded coordinates with no additional computational expense. In addition, the efficiency of multimodal image registration of the trunk will be enhanced by using a closed form solution based on an articulated model of the spine. This research program will first significantly contribute to the advancement of scientific research in the field of medical image registration by combining anatomically relevant representations with an original spectral embedding approach. Second, the proposed approach will ensure the reproducibility and the efficiency of multimodal image registration required in clinical applications, which will contribute toward technology transfer for healthcare. Third, this research program promotes the use of non invasive modalities in the diagnosis, prognosis and treatment outcome assessment of scoliosis, which will lead to enhanced quality of life for patients and reduced costs for the healthcare system.
医学图像配准是诊断、病理随访、治疗计划和模拟、术中辅助手术和治疗结果评估等各种临床应用中的一项重要任务。尽管研究界已经取得了巨大的进步,并且提出了大量用于模态内和多模态图像配准的复杂方法,但它们在临床环境中的适用性仍然有限。阻碍这些方法在临床应用中广泛使用的最重要的瓶颈不仅是它们的精度和鲁棒性,还有它们相关的计算成本。我们的研究项目的总体目标是进行基础和应用研究,以开发新的躯干解剖结构表征和配准算法,这些算法在非侵入性诊断、临床随访、手术计划和辅助治疗青少年特发性脊柱侧凸畸形方面具有很高的潜在影响。更具体地说,我们将使用光谱图理论,从非侵入式3D相机获得树干的三角网格表面的新表示。我们方法的新颖之处在于使用树干的解剖特征作为图节点的权重和额外的嵌入坐标,而不需要额外的计算开销。此外,通过使用基于脊柱关节模型的封闭形式解决方案,可以提高躯干多模态图像配准的效率。本研究计划将首先通过将解剖学相关表示与原始光谱嵌入方法相结合,为医学图像配准领域的科学研究的进步做出重大贡献。其次,所提出的方法将确保临床应用所需的多模态图像配准的可重复性和效率,这将有助于医疗保健技术转让。第三,本研究项目促进了在脊柱侧凸的诊断、预后和治疗结果评估中使用非侵入性模式,这将提高患者的生活质量,降低医疗保健系统的成本。
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(0)
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Cheriet, Farida其他文献
Mapping Pulsatile Optic Nerve Head Deformation Using OCT.
使用OCT映射脉动视神经头部变形。
- DOI:
10.1016/j.xops.2022.100205 - 发表时间:
2022-12 - 期刊:
- 影响因子:0
- 作者:
Solano, Marisse Masis;Richer, Emmanuelle;Cheriet, Farida;Lesk, Mark R.;Costantino, Santiago - 通讯作者:
Costantino, Santiago
Reliability of trunk shape measurements based on 3-D surface reconstructions
- DOI:
10.1007/s00586-007-0457-0 - 发表时间:
2007-11-01 - 期刊:
- 影响因子:2.8
- 作者:
Pazos, Valerie;Cheriet, Farida;Labelle, Hubert - 通讯作者:
Labelle, Hubert
Articulated Spine Models for 3-D Reconstruction From Partial Radiographic Data
- DOI:
10.1109/tbme.2008.2001125 - 发表时间:
2008-11-01 - 期刊:
- 影响因子:4.6
- 作者:
Boisvert, Jonathan;Cheriet, Farida;Ayache, Nicholas - 通讯作者:
Ayache, Nicholas
Joint segmentation and classification of retinal arteries/veins from fundus images
- DOI:
10.1016/j.artmed.2019.02.004 - 发表时间:
2019-03-01 - 期刊:
- 影响因子:7.5
- 作者:
Girard, Fantin;Kavalec, Conrad;Cheriet, Farida - 通讯作者:
Cheriet, Farida
Semiautomatic Detection of Scoliotic Rib Borders From Posteroanterior Chest Radiographs
- DOI:
10.1109/tbme.2011.2168394 - 发表时间:
2012-04-01 - 期刊:
- 影响因子:4.6
- 作者:
Plourde, Frederic;Cheriet, Farida;Dansereau, Jean - 通讯作者:
Dansereau, Jean
Cheriet, Farida的其他文献
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{{ truncateString('Cheriet, Farida', 18)}}的其他基金
Atlases and statistical modeling of vascular networks from medical images
医学图像血管网络的图谱和统计建模
- 批准号:
RGPIN-2018-05283 - 财政年份:2022
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
Atlases and statistical modeling of vascular networks from medical images
医学图像血管网络的图谱和统计建模
- 批准号:
RGPIN-2018-05283 - 财政年份:2021
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
Non-invasive 4D thoracic imaging infrastructure to support decision-making in the management of lung diseases in intensive care units (ICU).
无创 4D 胸部成像基础设施,支持重症监护病房 (ICU) 肺部疾病管理决策。
- 批准号:
RTI-2021-00595 - 财政年份:2020
- 资助金额:
$ 1.82万 - 项目类别:
Research Tools and Instruments
Atlases and statistical modeling of vascular networks from medical images
医学图像血管网络的图谱和统计建模
- 批准号:
RGPIN-2018-05283 - 财政年份:2020
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
Atlases and statistical modeling of vascular networks from medical images
医学图像血管网络的图谱和统计建模
- 批准号:
RGPIN-2018-05283 - 财政年份:2019
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
Modified version of CNN-based object detection for omnidirectional vision sensors
用于全向视觉传感器的基于 CNN 的目标检测的修改版本
- 批准号:
544090-2019 - 财政年份:2019
- 资助金额:
$ 1.82万 - 项目类别:
Engage Grants Program
Atlases and statistical modeling of vascular networks from medical images
医学图像血管网络的图谱和统计建模
- 批准号:
RGPIN-2018-05283 - 财政年份:2018
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
Anatomically Embedded Representations for Medical Image Registration in Clinical Applications
临床应用中医学图像配准的解剖嵌入式表示
- 批准号:
222860-2012 - 财政年份:2017
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
Anatomically Embedded Representations for Medical Image Registration in Clinical Applications
临床应用中医学图像配准的解剖嵌入式表示
- 批准号:
222860-2012 - 财政年份:2016
- 资助金额:
$ 1.82万 - 项目类别:
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Classification automatique des images de fond d'oeil
图像自动分类
- 批准号:
484993-2015 - 财政年份:2015
- 资助金额:
$ 1.82万 - 项目类别:
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