pykarambola: Minkowski tensor morphometry of 3D structures

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ID: 328676
2026
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Ranked #161 of 173 articles by views in Bioinformatics advances

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Abstract
Abstract Three-dimensional biological morphologies encode functional and physiological state, yet their directional, orientational, and topological properties are rarely captured by morphometric tools in bioimage analysis. Minkowski tensors encode surface curvature and directionality for arbitrary topologies; their eigensystems directly quantify elongation axes and anisotropy. A C ++ implementation, karambola, computes Minkowski tensors for triangulated surfaces but is inaccessible within Python-based bioimage workflows. We present pykarambola, a Python package that accepts NumPy arrays and standard mesh formats and returns Minkowski tensors, including derived anisotropy and orientation quantities. A high-level label-image interface converts three-dimensional integer arrays into per-object Minkowski tensors in a single call, making pykarambola directly compatible with the output of segmentation tools. An optional Cython extension accelerates graph-traversal steps of mesh initialization for large-scale analyses. Validated on synthetic meshes spanning three topologies and benchmarked on 1,584 adrenal gland meshes, pykarambola reproduces all 121 karambola features to near-floating-point agreement and is 2.8-fold faster, with speedups primarily attributable to per-object file input/output. pykarambola is freely available as an open-source software package. Availability and implementation: pykarambola is distributed under the BSD 3-Clause License and is available on GitHub at https://github.com/Ishihara-SynthMorph/pykarambola. It can be installed via pip.
Reference Key
openalex_W7213463233 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Yajushi Khurana, Keisuke Ishihara
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Journal Bioinformatics advances
Year 2026
DOI
10.1093/bioadv/vbag273
URL
https://doi.org/10.1093/bioadv/vbag273
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