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首页> 外文期刊>The Canadian Journal of Neurological Sciences: le Journal Canadien des Sciences Neurologiques >Image Analysis in Neuropathology: Hue-Saturation-Intensity vs. Colour Deconvolution
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Image Analysis in Neuropathology: Hue-Saturation-Intensity vs. Colour Deconvolution

机译：神经病理学图像分析：色调饱和 - 强度与颜色去卷积

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摘要

As image analysis expands into clinical and basic applications it is important that users be aware of opportunities and limitations. A common image analysis workflow involves the digitization of stained tissue sections into a red-green-blue (RGB) colour model for quantitative interpretation. Upstream of the digital image, quality and variability can be degraded at each step (tissue handling, fixation, sectioning, staining, image acquisition). Digital image analysis presents additional steps where variables can affect data quality. Image analysis platforms are not uniform. Aside from interface preferences, some introduce unintended variability due to their processing architecture that may not be obvious to the end-user. One important component of this is colour space representation: hue-saturation-intensity (HSI) vs. colour deconvolution (CD). A potential weakness of analyses within the HSI colour space is the mis-identification of darkly stained pixels, particularly when more than one stain is present. We were interested to discover whether HSI or CD provided greater fidelity in a typical immunoperoxidase/hematoxylin dataset.Fifty-nine samples were processed using HSI- and CD-based analyses. Processed image pairs were compared with the original sample to determine which processed image provided a more accurate representation. CD proved superior to HSI in 94.9% of the analyzed image pairs. Where the option exists, CD-based image analysis is strongly recommended.
机译：由于图像分析扩展到临床和基本应用中，用户意识到机会和限制是重要的。常见的图像分析工作流程涉及染色组织切片的数字化成红色蓝色（RGB）颜色模型，用于定量解释。在数字图像的上游，质量和可变性可以在每个步骤（组织处理，固定，切片，染色，图像采集）下降。数字图像分析显示了变量会影响数据质量的其他步骤。图像分析平台不统一。除了接口偏好之外，由于它们的处理架构，一些引入了意外的可变性，对最终用户可能并不明显。其中一个重要组成部分是颜色空间表示：色调饱和 - 强度（HSI）与颜色解卷积（CD）。 HSI色空间内的分析的潜在弱点是暗染色像素的误识别，特别是当存在多于一个染色时。我们有兴趣发现HSI或CD是否在典型的免疫氧化酶/苏木诺亚喹氏酶中提供了更大的保真度。使用基于HSI和CD的分析处理富含九个样品。将处理的图像对与原始样品进行比较，以确定提供哪个处理的图像提供更准确的表示。 CD在分析的图像对中94.9％的HSI证明了HSI。如果存在选项，强烈建议使用基于CD的图像分析。

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