Decomposition Atlases of Brains and Kidneys from Postmortem CT: Shape and Topological Data Analysis
Abstract
Forensic assessments of postmortem decomposition often rely on external, whole-body signs, yet structural changes within organs remain largely unquantified. Using whole-body computed tomography scans of 59 decedents from the New Mexico Decedent Image Database, we conduct an organ-level statistical shape analysis of decomposing brains and kidneys, representing each organ as a three-dimensional point cloud of its outer surface and internal cavity boundaries. Decomposition creates voids, fragmentation, and structural heterogeneity, complicating point correspondence. Registration-based principal component analysis and principal nested cones yield interpretable orderings for brains only. We therefore construct a registration-free pipeline using persistent homology and a fusion of complementary topological distances selected through simulations of cavity formation and growth. Clustering identifies broad patterns of internal decay, and seriation produces organ-specific decomposition atlases. The brain atlas combines geometric and topological rankings; the kidney atlas uses topology alone. Rank agreement is higher between paired kidneys (Kendall's τ= 0.59) than between brains and kidneys (τ= 0.34 to $0.39$), indicating asynchronous decompositions within a body. Whole-body stages agree more closely with brain than with kidney rankings. These findings support quantitative forensic taphonomy by complementing whole-body staging with organ-level, interior-based measurements. We release the organ point clouds and analysis code to support research on organ decomposition and shape analysis without reliable correspondence.
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BibTeX
@misc{zhan2026decomposition,
title = {{Decomposition Atlases of Brains and Kidneys from Postmortem CT: Shape and Topological Data Analysis}},
author = {Yanyan Zhan and Yuexuan Wu and Ian L. Dryden and Zeloso M. Tiago and Edward C. Schwalbe},
howpublished = {arXiv},
year = {2026},
month = nov,
doi = {10.48550/arxiv.2611.00278},
eprint = {2611.00278},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2611.00278},
}
RIS
TY - UNPB
TI - Decomposition Atlases of Brains and Kidneys from Postmortem CT: Shape and Topological Data Analysis
AU - Yanyan Zhan
AU - Yuexuan Wu
AU - Ian L. Dryden
AU - Zeloso M. Tiago
AU - Edward C. Schwalbe
PY - 2026
DA - 2026/11/01
PB - arXiv
DO - 10.48550/arxiv.2611.00278
UR - https://arxiv.org/abs/2611.00278
AB - Forensic assessments of postmortem decomposition often rely on external, whole-body signs, yet structural changes within organs remain largely unquantified. Using whole-body computed tomography scans of 59 decedents from the New Mexico Decedent Image Database, we conduct an organ-level statistical shape analysis of decomposing brains and kidneys, representing each organ as a three-dimensional point cloud of its outer surface and internal cavity boundaries. Decomposition creates voids, fragmentation, and structural heterogeneity, complicating point correspondence. Registration-based principal component analysis and principal nested cones yield interpretable orderings for brains only. We therefore construct a registration-free pipeline using persistent homology and a fusion of complementary topological distances selected through simulations of cavity formation and growth. Clustering identifies broad patterns of internal decay, and seriation produces organ-specific decomposition atlases. The brain atlas combines geometric and topological rankings; the kidney atlas uses topology alone. Rank agreement is higher between paired kidneys (Kendall's τ= 0.59) than between brains and kidneys (τ= 0.34 to $0.39$), indicating asynchronous decompositions within a body. Whole-body stages agree more closely with brain than with kidney rankings. These findings support quantitative forensic taphonomy by complementing whole-body staging with organ-level, interior-based measurements. We release the organ point clouds and analysis code to support research on organ decomposition and shape analysis without reliable correspondence.
ER -