# Micro-CT

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arXiv Nov 13, 2026
PoreTimeNet segments a whole micro-CT sequence at once, cutting carbonate porosity error from 0.97 to 0.28 points
A single time-resolved micro-CT experiment can yield tens to hundreds of three-dimensional images, and segmenting each one independently lets errors drift between frames and be mistaken for physical change. PoreTimeNet feeds several images from one temporal window through a shared spatial encoder and borrows information across time steps with temporal attention and decoder fusion. On a carbonate dissolution sequence its mean absolute porosity error was 0.28 percentage points against 0.97 for a 3D model that ignores temporal information, and rock boundary F1 rose from 0.833 to 0.941.
A single time-resolved micro-CT experiment can yield tens to hundreds of three-dimensional images, and segmenting each one independently lets errors drift between frames and be mistaken for physical change. PoreTimeNet feeds several images from one temporal window through a shared spatial encoder and borrows information across time steps with temporal attention and decoder fusion. On a carbonate dissolution sequence its mean absolute porosity error was 0.28 percentage points against 0.97 for a 3D model that ignores temporal information, and rock boundary F1 rose from 0.833 to 0.941.
Imperial College London
Zhuangzhuang Ma（First author）
PoreTimeNet Spatiotemporal Image Segmentation Swin Transformer Micro-CT
researchsquare.com Oct 14, 2026
Conglomerate digital rock stops choosing: wide-field scans recover pore detail, permeability error falls to 18.56%
To resolve the field-of-view versus resolution trade-off in micro-CT imaging of conglomerate reservoirs, Hy-MambaIR chains windowed self-attention with a Mamba state-space model into a local-to-global reconstruction network that recovers high-resolution pore and gravel structure from low-resolution wide-field slices. On paired multi-resolution micro-CT data it reaches a peak signal-to-noise ratio of 33.36 dB, 1.31 dB above HAT, and hits 30 dB with 6.6-fold fewer training iterations; on an 855³-voxel representative volume the mean relative error of three-directional absolute permeability is 18.56%, falling to 3.59% after supervised fine-tuning on pebbly sandstone.
To resolve the field-of-view versus resolution trade-off in micro-CT imaging of conglomerate reservoirs, Hy-MambaIR chains windowed self-attention with a Mamba state-space model into a local-to-global reconstruction network that recovers high-resolution pore and gravel structure from low-resolution wide-field slices. On paired multi-resolution micro-CT data it reaches a peak signal-to-noise ratio of 33.36 dB, 1.31 dB above HAT, and hits 30 dB with 6.6-fold fewer training iterations; on an 855³-voxel representative volume the mean relative error of three-directional absolute permeability is 18.56%, falling to 3.59% after supervised fine-tuning on pebbly sandstone.
China University of Petroleum, Beijing
Yumin Li（First author）Yang Zhang（Corresponding author）
Hy-MambaIR Image Super-Resolution Digital Rock Physics Mamba Transformer
American Journal of Respiratory Cell and Molecular Biology Oct 1, 2026
Four-region µCT analysis detects compensatory ventilation in the right caudal lobe of a mouse fibrosis model that whole-lung readouts miss
In 22 C57BL/6 mice (11 given triple oropharyngeal bleomycin at 0.25 mg/kg to induce pulmonary fibrosis and 11 given saline), respiratory-gated µCT was acquired at baseline and days 7, 14, and 21, a U-Net deep-learning algorithm segmented the lungs into left and right lobes that were further divided into apical and caudal regions using airway landmarks for four subregions, and regional volumes, aeration compartments, and ventilation maps were extracted; saline-treated mice showed stable metrics with minimal interanimal variability, whereas bleomycin-treated animals showed early and heterogeneous fibrotic changes with the apical regions most affected and the caudal-right region displaying a compensatory functional increase, so that µCT-based regional analysis detected localized dysfunction a
In 22 C57BL/6 mice (11 given triple oropharyngeal bleomycin at 0.25 mg/kg to induce pulmonary fibrosis and 11 given saline), respiratory-gated µCT was acquired at baseline and days 7, 14, and 21, a U-Net deep-learning algorithm segmented the lungs into left and right lobes that were further divided into apical and caudal regions using airway landmarks for four subregions, and regional volumes, aeration compartments, and ventilation maps were extracted; saline-treated mice showed stable metrics with minimal interanimal variability, whereas bleomycin-treated animals showed early and heterogeneous fibrotic changes with the apical regions most affected and the caudal-right region displaying a compensatory functional increase, so that µCT-based regional analysis detected localized dysfunction a
Politecnico di Milano Chiesi (France)University of Parma
Martina Buccardi（First author）Franco Fabio Stellari（Corresponding author）
Micro-CT Bleomycin-induced lung fibrosis mouse model Pulmonary Fibrosis Imaging biomarkers U-Net

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PoreTimeNet segments a whole micro-CT sequence at once, cutting carbonate porosity error from 0.97 to 0.28 points

Conglomerate digital rock stops choosing: wide-field scans recover pore detail, permeability error falls to 18.56%

Four-region µCT analysis detects compensatory ventilation in the right caudal lobe of a mouse fibrosis model that whole-lung readouts miss