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Automatic cell nuclei detection: a protocol to acquire multispectral images and to compare results between color and multispectral images

机译:自动细胞核检测:一种协议,用于获取多光谱图像并比较彩色和多光谱图像之间的结果

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摘要

High-throughput screening in histology and analysis need a necessary automatic cell or nucleus counting. Current methods and systems based on grayscale or color images give results with counting errors. We suggest to use multispectral imaging (with more than three bands) rather than color one for nucleus counting. A traditional acquisition chains uses a source of white light and a CCD camera in addition to the optical microscope. To pass to a multispectral acquisition, we use a Programmable Light Source (PLS) in the place of the white light source. This PLS is capable of generating different wavelengths in the visible spectrum. So, one color image and four multispectral images have been acquired from histological slices. The four multispectral images contain respectively 3 bands, 5 bands, 7 bands and 10 bands. To make a proper comparison of data, several considerations have been taken, (ike camera linearity, intensity difference between the wavebands from the PLS and non uniformity of the light intensity range in the images. So, a set of measures were done for calibrating the system. An automatic detection method based on segmentation by expectation-maximization and ellipse fitting is used. An extension of this method is proposed in order to be applied to multispectral images. The original and the extended method are then applied to the data previously acquired to have first results regarding the effect of using multispectral images rather than color ones.
机译:组织学和分析中的高通量筛选需要必要的自动细胞或细胞核计数。基于灰度或彩色图像的当前方法和系统给出带有计数误差的结果。我们建议使用多光谱成像(具有三个以上的波段),而不要使用一种颜色进行核计数。除了光学显微镜外,传统的采集链还使用白光源和CCD相机。为了传递到多光谱采集,我们使用可编程光源(PLS)代替白光源。该PLS能够在可见光谱中产生不同的波长。因此,已经从组织切片中获取了一个彩色图像和四个多光谱图像。四个多光谱图像分别包含3个波段,5个波段,7个波段和10个波段。为了进行适当的数据比较,已考虑了多个因素(如摄像机线性度,PLS波段之间的强度差异以及图像中光强度范围的不均匀性。因此,采取了一系列措施来校准提出了一种基于期望最大化和椭圆拟合的分割自动检测方法,对该方法进行了扩展,以应用于多光谱图像,然后将原始方法和扩展方法应用于先前获得的数据。关于使用多光谱图像而不是彩色图像的效果,我们获得了第一批结果。

著录项

  • 来源
  • 会议地点 San Francisco CA(US)
  • 作者单位

    Sciences and Technologies of Image and Telecommunications (SETIT) research unit, SfaxUniversity, Higher Institute of Biotechnology of Sfax, route de Soukra km3, 3038 Sfax, Tunisia,Le2i Lab., UMR CNRS 6306, Burgundy University, B.P. 47870, 21078 Dijon Cedex, France;

    Sciences and Technologies of Image and Telecommunications (SETIT) research unit, SfaxUniversity, Higher Institute of Biotechnology of Sfax, route de Soukra km3, 3038 Sfax, Tunisia;

    CellImaP, Federative Structure for Research 100, Burgundy University, B.P. 47870, 21079 Dijon Cedex, France;

    Sciences and Technologies of Image and Telecommunications (SETIT) research unit, SfaxUniversity, Higher Institute of Biotechnology of Sfax, route de Soukra km3, 3038 Sfax, Tunisia;

    Le2i Lab., UMR CNRS 6306, Burgundy University, B.P. 47870, 21078 Dijon Cedex, France;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Automatic cell nuclei detection; multispectral imaging; color imaging; acquisition protocol; image calibration;

    机译:自动细胞核检测;多光谱成像彩色成像;采集协议;影像校正;
  • 入库时间 2022-08-26 13:47:39

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