Longitudinal Modelling and Sequential Monitoring of Image Data Streams

图像数据流的纵向建模和顺序监控

基本信息

  • 批准号:
    1914639
  • 负责人:
  • 金额:
    $ 18万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2019
  • 资助国家:
    美国
  • 起止时间:
    2019-08-01 至 2023-07-31
  • 项目状态:
    已结题

项目摘要

In imaging applications related to earth and environmental monitoring, manufacturing industries, medical studies and many others, collected image data are often in the form of data streams in the sense that new images are acquired sequentially over time. In such applications, one fundamental task is to monitor the image sequence to see whether the underlying longitudinal process of the observed images changes significantly over time. This project aims to develop novel and effective statistical methods for answering this question. Because of the wide applications of image sequence monitoring, this project will have broader impacts on society through its applications in different disciplines and areas. Open source R packages will be developed and distributed freely for convenient use by practitioners. A web portal will also be developed for individual researchers to try the proposed methods. The PI plans to integrate the research results into educational activities, including the development of new curriculum modules, the mentoring of Ph.D. students, and outreach to local high schools students for after-school activities to raise their interests in data modeling and scientific research, and contribute to the workforce development in Science, Technology, Engineering and Mathematics. This project aims to develop a flexible longitudinal modeling approach and an effective sequential monitoring scheme for analyzing image data streams, and study their statistical properties. The proposed longitudinal model for describing observed images in a given time interval is flexible, and its estimation procedure has the edge-preservation property while removing noise. It can accommodate both geometric misalignments among observed images and spatio-temporal data correlation in the observed image data. The proposed image monitoring approach can account for dynamic longitudinal patterns of the observed image data streams. To this end, image pre-processing, including image denoising and image registration, will be performed properly before image monitoring. The proposed methods will consider both cases where the observation times are equally or unequally spaced.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
在与地球和环境监测、制造业、医学研究和许多其他相关的成像应用中,所收集的图像数据通常是数据流的形式,因为新图像是随时间顺序获取的。在这样的应用中,一个基本的任务是监视图像序列,以查看所观察到的图像的基本纵向过程是否随时间显著变化。该项目旨在开发新颖有效的统计方法来回答这个问题。由于图像序列监测的广泛应用,该项目将通过其在不同学科和领域的应用产生更广泛的社会影响。开源R包将免费开发和分发,以方便从业者使用。还将开发一个门户网站,供研究人员个人试用所提出的方法。PI计划将研究成果融入教育活动,包括开发新的课程模块,指导博士生,此外,我们亦会为本地中学生举办课外活动,以提高他们对数据建模及科学研究的兴趣,并为科学、技术、工程及数学方面的人才发展作出贡献。本计画旨在发展一种弹性的纵向模式化方法与一种有效的序列监控机制,以分析影像资料流,并研究其统计特性。所提出的描述给定时间间隔内观测图像的纵向模型是灵活的,并且其估计过程在去除噪声的同时具有边缘保持特性。该方法既能适应观测图像间的几何错位,又能适应观测图像数据的时空相关性。所提出的图像监测方法可以考虑所观察到的图像数据流的动态纵向图案。为此,将在图像监测之前适当地执行图像预处理,包括图像去噪和图像配准。该奖项反映了NSF的法定使命,并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

项目成果

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Peihua Qiu其他文献

Nonparametric monitoring of multiple count data
多重计数数据的非参数监控
  • DOI:
    10.1080/24725854.2018.1530486
  • 发表时间:
    2019-02
  • 期刊:
  • 影响因子:
    2.6
  • 作者:
    Peihua Qiu;Zhen He;Zhiqiong Wang
  • 通讯作者:
    Zhiqiong Wang
General Charting Scheme For Monitoring Serially Correlated Data With Short-Memory Dependence and Nonparametric Distributions
用于监控具有短记忆依赖性和非参数分布的序列相关数据的通用图表方案
  • DOI:
  • 发表时间:
  • 期刊:
  • 影响因子:
    2.6
  • 作者:
    Wendong Li;Peihua Qiu
  • 通讯作者:
    Peihua Qiu
Surveillance of cardiovascular diseases using a multivariate dynamic screening system
使用多变量动态筛查系统监测心血管疾病
  • DOI:
    10.1002/sim.6477
  • 发表时间:
    2015-06
  • 期刊:
  • 影响因子:
    2
  • 作者:
    Peihua Qiu;Dongdong Xiang
  • 通讯作者:
    Dongdong Xiang
Reliable Post-Signal Fault Diagnosis for Correlated High-Dimensional Data Streams
相关高维数据流的可靠信号后故障诊断
  • DOI:
    10.1080/00401706.2021.1979100
  • 发表时间:
  • 期刊:
  • 影响因子:
    2.5
  • 作者:
    Dongdong Xiang;Peihua Qiu;Dezhi Wang;Wendong Li
  • 通讯作者:
    Wendong Li
Surface-Enhanced Third-Order Nonlinear Optical Response of C 60 Films on Roughed Glass Plate
粗化玻璃板上 C 60 薄膜的表面增强三阶非线性光学响应
  • DOI:
    10.1088/0256-307x/10/10/007
  • 发表时间:
    1993
  • 期刊:
  • 影响因子:
    3.5
  • 作者:
    Shijie Li;Xiaoping Xu;Wen;Peihua Qiu;Wenyao Wang
  • 通讯作者:
    Wenyao Wang

Peihua Qiu的其他文献

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{{ truncateString('Peihua Qiu', 18)}}的其他基金

New Methods for Sequential Monitoring of Longitudinal Patterns
纵向模式顺序监测的新方法
  • 批准号:
    1405698
  • 财政年份:
    2014
  • 资助金额:
    $ 18万
  • 项目类别:
    Continuing Grant
Intensity-Based Image Registration and 3-D Image Denoising
基于强度的图像配准和 3D 图像去噪
  • 批准号:
    1007506
  • 财政年份:
    2010
  • 资助金额:
    $ 18万
  • 项目类别:
    Standard Grant
Statistical Analysis of Image Restoration and Its Applications in Magnetic Resonance Imaging
图像恢复统计分析及其在磁共振成像中的应用
  • 批准号:
    0706082
  • 财政年份:
    2007
  • 资助金额:
    $ 18万
  • 项目类别:
    Continuing Grant
Image Segmentation for cDNA Microarray Data and Jump-Preserving Surface Estimation
cDNA 微阵列数据的图像分割和跳跃保持表面估计
  • 批准号:
    0406020
  • 财政年份:
    2004
  • 资助金额:
    $ 18万
  • 项目类别:
    Standard Grant

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