PyCellMech: A shape-based feature extraction pipeline for use in medical and biological studies

TL;DR

PyCellMech is a comprehensive, open-source Python package designed to extract a wide range of shape-based features from medical and biological images, facilitating research in disease prevention and treatment.

Contribution

It introduces a unified tool that consolidates various shape feature extraction methods into one accessible package, filling a notable gap in existing tools.

Findings

Provides easy extraction of shape features for medical images

Supports three classes of shape features: one-dimensional, geometric, polygonal

Will be expanded to include additional feature classes in future versions

Abstract

Summary: Medical researchers obtain knowledge about the prevention and treatment of disability and disease using physical measurements and image data. To assist in this endeavor, feature extraction packages are available that are designed to collect data from the image structure. In this study, we aim to augment current works by adding to the current mix of shape-based features. The significance of shape-based features has been explored extensively in research for several decades, but there is no single package available in which all shape-related features can be extracted easily by the researcher. PyCellMech has been crafted to address this gap. The PyCellMech package extracts three classes of shape features, which are classified as one-dimensional, geometric, and polygonal. Future iterations will be expanded to include other feature classes, such as scale-space. Availability and implementation: PyCellMech is freely available at https://github.com/icm-dac/pycellmech.