Paper Citation Record · LEDGER

From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data

As of 23 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2607.12175.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2607.12175 v3

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Outbound references

Observation accb54a7-dcbe-4215-8c32-09e60a7ffe4c · outbound

This paper cites Using X-ray tomography, the 3D morphology and distribution of different phases, regions of interest and defects such as pores, cracks and fractures can be analyzed [4].

From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data Using X-ray tomography, the 3D morphology and distribution of different phases, regions of interest and defects such as pores, cracks and fractures can be analyzed [4]

Reference 1

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This paper cites The annotated dataset consisted of 25 reconstructed 2D slices selected from five tomography scans/material systems.

From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data The annotated dataset consisted of 25 reconstructed 2D slices selected from five tomography scans/material systems

Reference 2

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From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data Unresolved cited work

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From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data Unresolved cited work

Reference 4

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This paper cites We also thank Dr.

From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data We also thank Dr

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From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data Unresolved cited work

Reference 7

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This paper cites X-ray-transmission computed tomography,.

From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data X-ray-transmission computed tomography,

Reference 8

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This paper cites X-ray microtomography of biological tissues using laboratory and synchrotron sources,.

From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data X-ray microtomography of biological tissues using laboratory and synchrotron sources,

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This paper cites An introduction to the application of X-ray microtomography to the three-dimensional study of igneous rocks,.

From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data An introduction to the application of X-ray microtomography to the three-dimensional study of igneous rocks,

Reference 10

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This paper cites Kirkendall pore evolution during interdiffusion and homogenization of titanium-coated nickel microwires,.

From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data Kirkendall pore evolution during interdiffusion and homogenization of titanium-coated nickel microwires,

Reference 11

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From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data Unresolved cited work

Reference 12

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This paper cites AI@ALS Workshop Report: Machine Learning Needs at the Advanced Light Source,.

From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data AI@ALS Workshop Report: Machine Learning Needs at the Advanced Light Source,

Reference 13

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This paper cites A workflow for segmenting soil and plant X-ray computed tomography images with deep learning in Google’s Colaboratory,.

From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data A workflow for segmenting soil and plant X-ray computed tomography images with deep learning in Google’s Colaboratory,

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This paper cites UNeXt: MLP-Based Rapid Medical Image Segmentation Network,.

From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data UNeXt: MLP-Based Rapid Medical Image Segmentation Network,

Reference 15

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This paper cites Loss weightings for improving imbalanced brain structure segmentation using fully convolutional networks,.

From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data Loss weightings for improving imbalanced brain structure segmentation using fully convolutional networks,

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This paper cites Semantic segmentation of small objects and modeling of uncertainty in urban remote sensing images using deep convolutional neural networks,.

From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data Semantic segmentation of small objects and modeling of uncertainty in urban remote sensing images using deep convolutional neural networks,

Reference 17

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From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data A review on image segmentation techniques,

Reference 18

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This paper cites A threshold selection method from gray-level histograms,.

From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data A threshold selection method from gray-level histograms,

Reference 19

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From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data Various image segmentation techniques: A review,

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From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data Statistical region merging,

Reference 21

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From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data Unresolved cited work

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From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data Deep watershed transform for instance segmentation,

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From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data Threshold selection based on cluster analysis,

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From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data Insight into 3D micro-CT data: exploring segmentation algorithms through performance metrics,

Reference 25

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From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data U-Net: Convolutional networks for biomedical image segmentation,

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From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data Fully convolutional networks for semantic segmentation,

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From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data ImageJ2,

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From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data Montreal, QC, Canada: Object Research Systems

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From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data Image segmentation using deep learning: A survey,

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From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data U-Net and its variants for medical image segmentation: A review of theory and applications,

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From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data An efficient interactive multi-label segmentation tool for 2D and 3D medical images using fully connected conditional random field,

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From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data Every annotation counts: Multi-label deep supervision for medical image segmentation,

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From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data Class-balanced random patch training to address class imbalance in tiling-based farmland classification,

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From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data A ConvNet for the 2020s,

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From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data Deep residual learning for image recognition,

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From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data Aggregated residual transformations for deep neural networks,

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From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data Feature pyramid networks for object detection,

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From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data Gaussian Error Linear Units (GELUs)

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From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data Learning deep latent space for multi-label classification,

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From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data Measures of the amount of ecologic association between species,

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From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data Hydro-mechanical measurements of sheared crystalline rock fractures with applications for EGS Collab Experiments 1 and 2,

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From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data Fracture evolution in multimineral systems: The role of mineral composition, flow rate, and fracture aperture heterogeneity,

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From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data Correlative X-ray micro-nanotomography with scanning electron microscopy at the Advanced Light Source,

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From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data Your ViT is secretly an image segmentation model,

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From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data DINOv2: Learning Robust Visual Features without Supervision

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