Medical Image Compression

医学图像压缩

基本信息

  • 批准号:
    171073-2013
  • 负责人:
  • 金额:
    $ 1.75万
  • 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:
    2017
  • 资助国家:
    加拿大
  • 起止时间:
    2017-01-01 至 2018-12-31
  • 项目状态:
    已结题

项目摘要

Prompt access to clinical information is crucial for improved healthcare decisions. The Electronic Health Record (EHR) promises better care by providing centralized access to the different sources of data that make up the patient's medical record. EHR is expected to help achieve a more efficient health-care system by enhancing productivity through timely access to information; it is also expected to help achieve a more effective system by reducing the duplication of tests. Medical images are very important information in the patient's health record. With Canada Health Infoway's investment in diagnostic imaging projects, medical images are centrally archived for easier long-term management. Images are also being shared and accessed by a very large number of healthcare professionals: by clinicians as part of a patient's follow-up and treatment; by radiologists to provide second opinions or first opinions when no radiologists are on site for trauma or remote-area cases; or by specialized physicians, such as surgeons or orthopedists, in planning surgical operations or procedures. The size of medical images is continuously growing. Computed Tomography (CT), for example, can generate a series of thousands of images whose size exceeds the gigabyte. Transferring large image sets on a communication network requires an enormous bandwidth, resulting in an inefficient and inadequate system. Images can be compressed with no information loss, reducing their size by 30%. Further compressing is needed, but currently available methods introduce artifacts and distortions that may impact diagnostic accuracy. In this research program, we propose to quantitatively assess the impact of compression methods on the diagnostic value of medical images. We also propose to develop novel compression schemes specially tailored to preserve that diagnostic value. Therefore, we expect to reduce the bandwidth needed to transfer medical images while preserving their diagnostic value.
及时获取临床信息对于改善医疗决策至关重要。电子健康记录(EHR)通过提供对构成患者病历的不同数据源的集中访问,承诺提供更好的护理。预计电子健康记录将通过及时获取信息提高生产力,从而帮助实现更有效的保健系统;还预计将通过减少重复检测,帮助实现更有效的系统。医学图像是患者健康记录中非常重要的信息。随着Canada Health Infoway对诊断成像项目的投资,医疗图像被集中存档,以便于长期管理。大量的医疗保健专业人员也在共享和访问图像:临床医生作为患者随访和治疗的一部分;放射科医生在没有放射科医生现场治疗创伤或偏远地区病例时提供第二意见或第一意见;或者由专业医生,如外科医生或整形外科医生,在计划外科手术或程序时。医学图像的尺寸不断增长。例如,计算机断层扫描(CT)可以生成一系列数千张图像,其大小超过千兆字节。在通信网络上传输大型图像集需要巨大的带宽,导致系统效率低下且不充分。图像可以在没有信息丢失的情况下被压缩,大小减少了30%。需要进一步压缩,但目前可用的方法引入了可能影响诊断准确性的伪影和失真。在这项研究计划中,我们建议定量评估压缩方法对医学图像诊断价值的影响。我们还建议开发新的压缩方案,特别是量身定制,以保持诊断价值。因此,我们希望减少传输医学图像所需的带宽,同时保留其诊断价值。

项目成果

期刊论文数量(0)
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会议论文数量(0)
专利数量(0)

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Noumeir, Rita其他文献

Inflight Broadband Connectivity Using Cellular Networks
  • DOI:
    10.1109/access.2016.2537648
  • 发表时间:
    2016-01-01
  • 期刊:
  • 影响因子:
    3.9
  • 作者:
    Tadayon, Navid;Kaddoum, Georges;Noumeir, Rita
  • 通讯作者:
    Noumeir, Rita
Arterial Partial Pressures of Carbon Dioxide Estimation Using Non-Invasive Parameters in Mechanically Ventilated Children
Infrared and 3D Skeleton Feature Fusion for RGB-D Action Recognition
  • DOI:
    10.1109/access.2020.3023599
  • 发表时间:
    2020-01-01
  • 期刊:
  • 影响因子:
    3.9
  • 作者:
    De Boissiere, Alban Main;Noumeir, Rita
  • 通讯作者:
    Noumeir, Rita
Vision-Based Fall Detection Using ST-GCN
  • DOI:
    10.1109/access.2021.3058219
  • 发表时间:
    2021-01-01
  • 期刊:
  • 影响因子:
    3.9
  • 作者:
    Keskes, Oussema;Noumeir, Rita
  • 通讯作者:
    Noumeir, Rita
Using machine learning models to predict oxygen saturation following ventilator support adjustment in critically ill children: A single center pilot study
  • DOI:
    10.1371/journal.pone.0198921
  • 发表时间:
    2019-02-20
  • 期刊:
  • 影响因子:
    3.7
  • 作者:
    Ghazal, Sam;Sauthier, Michael;Noumeir, Rita
  • 通讯作者:
    Noumeir, Rita

Noumeir, Rita的其他文献

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{{ truncateString('Noumeir, Rita', 18)}}的其他基金

Decision support for the intensive care
重症监护决策支持
  • 批准号:
    RGPIN-2019-06205
  • 财政年份:
    2022
  • 资助金额:
    $ 1.75万
  • 项目类别:
    Discovery Grants Program - Individual
Decision support for the intensive care
重症监护的决策支持
  • 批准号:
    RGPIN-2019-06205
  • 财政年份:
    2021
  • 资助金额:
    $ 1.75万
  • 项目类别:
    Discovery Grants Program - Individual
An intelligent vision-based system for detecting self-harm behavior
用于检测自残行为的基于智能视觉的系统
  • 批准号:
    523637-2018
  • 财政年份:
    2020
  • 资助金额:
    $ 1.75万
  • 项目类别:
    Collaborative Research and Development Grants
Decision support for the intensive care
重症监护的决策支持
  • 批准号:
    RGPIN-2019-06205
  • 财政年份:
    2020
  • 资助金额:
    $ 1.75万
  • 项目类别:
    Discovery Grants Program - Individual
An intelligent vision-based system for detecting self-harm behavior
用于检测自残行为的基于智能视觉的系统
  • 批准号:
    523637-2018
  • 财政年份:
    2019
  • 资助金额:
    $ 1.75万
  • 项目类别:
    Collaborative Research and Development Grants
Decision support for the intensive care
重症监护的决策支持
  • 批准号:
    RGPIN-2019-06205
  • 财政年份:
    2019
  • 资助金额:
    $ 1.75万
  • 项目类别:
    Discovery Grants Program - Individual
An intelligent vision-based system for detecting self-harm behavior
用于检测自残行为的基于智能视觉的系统
  • 批准号:
    523637-2018
  • 财政年份:
    2018
  • 资助金额:
    $ 1.75万
  • 项目类别:
    Collaborative Research and Development Grants
Intelligent surveillance for event detection
事件检测的智能监控
  • 批准号:
    498033-2016
  • 财政年份:
    2016
  • 资助金额:
    $ 1.75万
  • 项目类别:
    Engage Plus Grants Program
Real-time telemedicine for emergency medical evacuation by air transportation
通过航空运输进行紧急医疗后送的实时远程医疗
  • 批准号:
    465644-2014
  • 财政年份:
    2015
  • 资助金额:
    $ 1.75万
  • 项目类别:
    Collaborative Research and Development Grants
Medical Image Compression
医学图像压缩
  • 批准号:
    171073-2013
  • 财政年份:
    2015
  • 资助金额:
    $ 1.75万
  • 项目类别:
    Discovery Grants Program - Individual

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相似海外基金

SBIR Phase I: Improved image compression targeting machine learning based detection algorithms
SBIR 第一阶段:针对基于机器学习的检测算法改进图像压缩
  • 批准号:
    2233091
  • 财政年份:
    2023
  • 资助金额:
    $ 1.75万
  • 项目类别:
    Standard Grant
Human Visual Properties based Image/Video Compression Research
基于人类视觉特性的图像/视频压缩研究
  • 批准号:
    22K17921
  • 财政年份:
    2022
  • 资助金额:
    $ 1.75万
  • 项目类别:
    Grant-in-Aid for Early-Career Scientists
Image and Video Compression Meets Computer Vision
图像和视频压缩与计算机视觉的结合
  • 批准号:
    RGPIN-2020-04525
  • 财政年份:
    2022
  • 资助金额:
    $ 1.75万
  • 项目类别:
    Discovery Grants Program - Individual
Improved Treatment of Vertebral Compression Fractures for Elderly Patients Using an Image-Guided, Percutaneous Delivery of a Novel Bone Adhesive
使用图像引导、经皮输送新型骨粘合剂改善老年患者椎体压缩性骨折的治疗
  • 批准号:
    10547209
  • 财政年份:
    2022
  • 资助金额:
    $ 1.75万
  • 项目类别:
Image and Video Compression Meets Computer Vision
图像和视频压缩与计算机视觉的结合
  • 批准号:
    RGPIN-2020-04525
  • 财政年份:
    2021
  • 资助金额:
    $ 1.75万
  • 项目类别:
    Discovery Grants Program - Individual
AI-based Image and Video Compression on Mobile Neural Accelerators
移动神经加速器上基于人工智能的图像和视频压缩
  • 批准号:
    78200
  • 财政年份:
    2020
  • 资助金额:
    $ 1.75万
  • 项目类别:
    Collaborative R&D
Image and Video Compression Meets Computer Vision
图像和视频压缩与计算机视觉的结合
  • 批准号:
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  • 财政年份:
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  • 资助金额:
    $ 1.75万
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提高JPEG图像压缩算法的效率
  • 批准号:
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  • 财政年份:
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  • 资助金额:
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Biological Image and Video Compression
生物图像和视频压缩
  • 批准号:
    105768
  • 财政年份:
    2019
  • 资助金额:
    $ 1.75万
  • 项目类别:
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Study on the application of machine learning technologies to image compression coding
机器学习技术在图像压缩编码中的应用研究
  • 批准号:
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  • 财政年份:
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