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gtexture: Generalized Application of Co-Occurrence Matrices and Haralick Texture
Generalizes application of gray-level co-occurrence matrix (GLCM) metrics to objects outside of images. The current focus is to apply GLCM metrics to the study of biological networks and fitness landscapes that are used in studying evolutionary medicine and biology, particularly the evolution of cancer resistance. The package was developed as part of the author's publication in Physics in Medicine and Biology Barker-Clarke et al. (2023) <doi:10.1088/1361-6560/ace305>. A general reference to learn more about mathematical oncology can be found at Rockne et al. (2019) <doi:10.1088/1478-3975/ab1a09>.
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Package details |
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| Author | Rowan Barker-Clarke [aut, cre] (ORCID: <https://orcid.org/0000-0003-1961-7919>), Raoul Wadhwa [aut] (ORCID: <https://orcid.org/0000-0003-0503-9580>), Davis Weaver [aut], Jacob Scott [aut] (ORCID: <https://orcid.org/0000-0003-2971-7673>) |
| Maintainer | Rowan Barker-Clarke <rowanbarkerclarke@gmail.com> |
| License | MIT + file LICENSE |
| Version | 1.0.1 |
| URL | https://rbarkerclarke.github.io/gtexture/ |
| Package repository | View on CRAN |
| Installation |
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