Contour Analysis Tool: an interactive tool for background and morphology analysis

Mark A. Hutchison, Christine M. Koepferl
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Abstract

We introduce the Contour Analysis Tool (CAT), a Python toolkit aimed at identifying and analyzing structural elements in density maps. CAT employs various contouring techniques, including the lowest-closed contour (LCC), linear and logarithmic Otsu thresholding, and average gradient thresholding. These contours can aid in foreground and background segmentation, providing natural limits for both, as well as edge detection and structure identification. Additionally, CAT provides image processing methods such as smoothing, background removal, and image masking. The toolkit features an interactive suite of controls designed for Jupyter environments, enabling users to promptly visualize the effects of different methods and parameters. We describe, test, and demonstrate the performance of CAT, highlighting its potential use cases. CAT is publicly available on GitHub, promoting accessibility and collaboration.
轮廓分析工具:用于背景和形态分析的交互式工具
我们介绍轮廓分析工具(CAT),这是一个 Python 工具包,旨在识别和分析密度图中的结构元素。CAT 采用了多种轮廓分析技术,包括最低闭合轮廓(LCC)、线性和对数大津阈值分析以及平均梯度阈值分析。这些轮廓分析技术可帮助进行前景和背景分割,为前景和背景分割以及边缘检测和结构识别提供自然限制。此外,CAT 还提供了图像处理方法,如平滑、背景去除和图像屏蔽。该工具包拥有一套专为 Jupyter 环境设计的交互式控件,使用户能够及时直观地看到不同方法和参数的效果。我们对 CAT 的性能进行了描述、测试和演示,并重点介绍了其潜在的使用案例。CAT 在 GitHub 上公开发布,促进了可访问性和协作性。
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