A computer aided chromosome imaging technique for cancer diagnosis

用于癌症诊断的计算机辅助染色体成像技术

基本信息

  • 批准号:
    7841805
  • 负责人:
  • 金额:
    $ 31.39万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2006
  • 资助国家:
    美国
  • 起止时间:
    2006-07-14 至 2013-05-31
  • 项目状态:
    已结题

项目摘要

DESCRIPTION (provided by applicant): Identification of recurrent chromosomal aberrations is important for diagnosis, prognosis, and therapy of most hematological malignancies. Due to difficulties with culture of tumor cells, low mitotic index, poor chromosomal morphologies, and low prevalence, it takes tremendous effort and time for a cytogenetic clinician to obtain a sufficient number of analyzable metaphase cells under microscope before he/she can make an accurate clinical diagnosis. This process is not only very inefficient but also subject to human errors. In order to improve the efficiency and accuracy of leukemia diagnosis, we propose to develop a computer aided chromosome imaging technique. Specifically, we will develop an innovative high-speed microscopic imaging system based on a time-delay-integration technique. The system can scan the entire sample-slide at high magnification to obtain high resolution digital images to reveal metaphase chromosomes as required by clinical diagnosis. We will also develop a novel computer aided diagnosis (CAD) scheme including four specific modules to (1) detect analyzable metaphase chromosome cells, (2) segment overlapped chromosomes, (3) identify and classify distorted chromosomes associated with cancer cells, and (4) predict the cancer prognosis. After identification and segmentation of analyzable chromosomes, we will compute and search for the effective and robust image features. Genetic algorithm will be used to train and optimize an artificial neural network and a Bayesian belief network for the classification and prediction tasks, respectively. Using the integrated CAD workstation, we will conduct an observer performance study to assess the performance of the technique and its clinical feasibility. In summary, the proposed imaging technique is highly efficient, and no or only minimal human interventions are required from initial slide-scanning up to the presentation of CAD results. With such a new computerized clinical tool, cytogeneticists can effectively focus their efforts on analyzing/verifying chromosomal abnormal patterns and making final diagnostic decisions. It is therefore expected that the proposed technology can significantly improve the efficiency and accuracy of cancer (i.e., leukemia) diagnosis. The proposed technique has significant clinical potentials in monitoring therapeutic efficacy of cancer treatment as well.
描述(由申请人提供):识别复发性染色体畸变对于大多数血液恶性肿瘤的诊断、预后和治疗非常重要。由于肿瘤细胞的培养困难、有丝分裂指数低、染色体形态差和患病率低,细胞遗传学临床医生需要花费大量的精力和时间在显微镜下获得足够数量的可分析中期细胞,然后才能做出准确的临床诊断。这个过程不仅效率很低,而且容易出现人为错误。为了提高白血病诊断的效率和准确性,我们提出了一种计算机辅助染色体成像技术。具体来说,我们将开发一种创新的高速显微成像系统的基础上的时间延迟积分技术。该系统可以在高放大率下扫描整个样品载玻片,以获得高分辨率的数字图像,以显示临床诊断所需的中期染色体。我们还将开发一种新的计算机辅助诊断(CAD)方案,包括四个特定模块:(1)检测可分析的中期染色体细胞,(2)分割重叠染色体,(3)识别和分类与癌细胞相关的畸变染色体,以及(4)预测癌症预后。在识别和分割可分析的染色体后,我们将计算和搜索有效的和鲁棒的图像特征。遗传算法将被用来训练和优化人工神经网络和贝叶斯信念网络的分类和预测任务,分别。使用集成CAD工作站,我们将进行观察者性能研究,以评估该技术的性能及其临床可行性。总之,所提出的成像技术是高效的,并且从最初的载玻片扫描到CAD结果的呈现不需要或仅需要最少的人工干预。有了这样一个新的计算机化的临床工具,细胞遗传学家可以有效地集中精力分析/验证染色体异常模式,并作出最终的诊断决定。因此预期所提出的技术可以显著提高癌症的效率和准确性(即,白血病)诊断。所提出的技术在监测癌症治疗的疗效方面也具有重要的临床潜力。

项目成果

期刊论文数量(13)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Evaluations of auto-focusing methods under a microscopic imaging modality for metaphase chromosome image analysis.
The impact of the condenser on cytogenetic image quality in digital microscope system.
Automated identification of analyzable metaphase chromosomes depicted on microscopic digital images.
自动识别显微数字图像上描绘的可分析中期染色体。
  • DOI:
    10.1016/j.jbi.2007.06.008
  • 发表时间:
    2008
  • 期刊:
  • 影响因子:
    4.5
  • 作者:
    Wang,Xingwei;Li,Shibo;Liu,Hong;Wood,Marc;Chen,WeiR;Zheng,Bin
  • 通讯作者:
    Zheng,Bin
Development and Assessment of an Integrated Computer-Aided Detection Scheme for Digital Microscopic Images of Metaphase Chromosomes.
中期染色体数字显微图像集成计算机辅助检测方案的开发和评估。
  • DOI:
    10.1117/1.3013459
  • 发表时间:
    2008
  • 期刊:
  • 影响因子:
    1.1
  • 作者:
    Wang,Xingwei;Zheng,Bin;Li,Shibo;Mulvihill,JohnJ;Liu,Hong
  • 通讯作者:
    Liu,Hong
Continuous in vitro exposure to low-dose genistein induces genomic instability in breast epithelial cells.
体外连续暴露于低剂量金雀异黄素会导致乳腺上皮细胞基因组不稳定。
  • DOI:
    10.1016/j.cancergencyto.2008.06.010
  • 发表时间:
    2008
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Kim,YoungMi;Yang,Shihe;Xu,Weihong;Li,Shibo;Yang,Xiaohe
  • 通讯作者:
    Yang,Xiaohe
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Hong Liu其他文献

Hong Liu的其他文献

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{{ truncateString('Hong Liu', 18)}}的其他基金

Medical Imaging Technology Development Core
医学影像技术开发核心
  • 批准号:
    10334983
  • 财政年份:
    2022
  • 资助金额:
    $ 31.39万
  • 项目类别:
Medical Imaging Technology Development Core
医学影像技术开发核心
  • 批准号:
    10573274
  • 财政年份:
    2022
  • 资助金额:
    $ 31.39万
  • 项目类别:
Functions and Regulation of Centromeric Transcription
着丝粒转录的功能和调控
  • 批准号:
    10604267
  • 财政年份:
    2021
  • 资助金额:
    $ 31.39万
  • 项目类别:
Functions and Regulation of Centromeric Transcription
着丝粒转录的功能和调控
  • 批准号:
    10179898
  • 财政年份:
    2021
  • 资助金额:
    $ 31.39万
  • 项目类别:
Functions and Regulation of Centromeric Transcription
着丝粒转录的功能和调控
  • 批准号:
    10379263
  • 财政年份:
    2021
  • 资助金额:
    $ 31.39万
  • 项目类别:
Timing Control of Centromeric Cohesion through Centromere-localized Sgo1
通过着丝粒定位的 Sgo1 控制着丝粒凝聚的时间
  • 批准号:
    10249286
  • 财政年份:
    2018
  • 资助金额:
    $ 31.39万
  • 项目类别:
Automated FISH Imaging and Analysis for Screening Cervical Cancer
用于筛查宫颈癌的自动化 FISH 成像和分析
  • 批准号:
    7566142
  • 财政年份:
    2009
  • 资助金额:
    $ 31.39万
  • 项目类别:
A computer aided chromosome imaging technique for cancer diagnosis
用于癌症诊断的计算机辅助染色体成像技术
  • 批准号:
    7609064
  • 财政年份:
    2006
  • 资助金额:
    $ 31.39万
  • 项目类别:
A computer aided chromosome imaging technique for cancer diagnosis
用于癌症诊断的计算机辅助染色体成像技术
  • 批准号:
    7423851
  • 财政年份:
    2006
  • 资助金额:
    $ 31.39万
  • 项目类别:
A computer aided chromosome imaging technique for cancer diagnosis
用于癌症诊断的计算机辅助染色体成像技术
  • 批准号:
    7088672
  • 财政年份:
    2006
  • 资助金额:
    $ 31.39万
  • 项目类别:

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