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HISTOLOGICAL IMAGE DETECTION USING STATISTICAL TESTS AND A NEURAL NETWORK

机译:使用统计测试和神经网络进行组织图像检测

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Many methods have been developed for image edge detection and most of these techniques work well in images with uniform regions, but less well in regions with greater non-uniformity. This paper describes an edge enhancing technique suitable for the complexity of histological images, such as those contained in the Mouse Embryo Atlas (MA), In order to achieve this, a new feature exaction method has been developed which combines a neural network technique with a novel edge detection algorithm. The neural network has been trained on several sets of appropriate images that classify a selection of pixels as edge or non-edge points. Our preliminary results are promising showing that many edges have been successfully enhanced with few false positives.
机译:已经开发出许多用于图像边缘检测的方法,并且这些技术中的大多数在具有均匀区域的图像中效果很好,但是在具有较大不均匀性的区域中效果较差。本文介绍了一种适用于组织学图像复杂性的边缘增强技术,例如包含在Mouse Embryo Atlas(MA)中的图像。为实现此目的,已开发出一种新的特征提取方法,该方法将神经网络技术与基于神经网络技术相结合。新颖的边缘检测算法。已经在几组适当的图像上训练了神经网络,这些图像将对像素的选择分类为边缘点或非边缘点。我们的初步结果令人鼓舞,表明许多边缘都得到了成功的增强,几乎没有误报。

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