Work

Bio-Volumentations: A Python library for augmentation of volumetric image sequences

Year: 2025

Type: software-paper

Abstract: Data augmentation is a widely used technique to increase generalization ability of deep learning models, especially when dealing with sparse training data. It is also crucial in biomedical applications, where annotated images are extremely rare due to high image dimensionality and expensive data acquisition processes. However, existing image augmentation toolboxes are not suitable for biomedical applications: they usually only support low-dimensional images or very few annotation types. To address this issue, we developed Bio-Volumentations —a Python library for transforming multidimensional biomedical images with image- and point-based annotations. Thanks to its universality, user-friendly interface, and independence of deep learning toolboxes, it facilitates efficient data preprocessing and augmentation in various computer vision tasks.

Source: SoftwareX

DOI: 10.1016/j.softx.2025.102151

Authors: Lucia Hradecká, Filip Lux, Samuel Šul’an, Petr Matula

Institution: Masaryk University

Language: English

Topic: Medical Image Segmentation Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,200

Funder: Grantová Agentura České Republiky