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

TL;DR

The paper presents the Contour Analysis Tool (CAT), an interactive Python toolkit for analyzing structural elements in density maps through contouring, segmentation, and image processing, with a focus on usability in Jupyter environments.

Contribution

The paper introduces CAT, a novel interactive toolkit that combines multiple contouring and image processing techniques for structural analysis in density maps, optimized for Jupyter notebooks.

Findings

Effective contouring and segmentation demonstrated on density maps

Interactive controls facilitate parameter tuning and visualization

Open-source availability encourages community use and development

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.