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Paper Citation Record · LEDGER

Explaining 3D Computed Tomography Classifiers with Counterfactuals

As of 8 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 1 inbound Pith citation observation for arXiv:2502.07156.

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

pith.paper-citation-record.v1
2502.07156 v2

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T13:39:52.610321Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:08:26.538990Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-07T15:08:31.886270Z

Reference resolution

23 of 23 outbound references displayed

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External citation measurements

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Outbound references

Observation 473bee02-fa72-4903-b445-bb493a698d3a · outbound

This paper cites an unresolved cited work.

Explaining 3D Computed Tomography Classifiers with Counterfactuals Unresolved cited work

Reference 1

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Observation 8a0dc53f-ce8b-4ec1-ae34-ca0befe3ce66 · outbound

This paper cites Shah, Andrew Johnston, Robert D.

Explaining 3D Computed Tomography Classifiers with Counterfactuals Shah, Andrew Johnston, Robert D

Reference 2

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Observation 0eb3de93-81b0-4b09-98ec-22b8ad09e3f0 · outbound

This paper cites Lungren, and Akshay Chaudhari.

Explaining 3D Computed Tomography Classifiers with Counterfactuals Lungren, and Akshay Chaudhari

Reference 3

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Observation d80a1cd0-384a-4120-a0cc-2cff74b6ed35 · outbound

This paper cites Taming transformers for high-resolution image synthesis.

Explaining 3D Computed Tomography Classifiers with Counterfactuals Taming transformers for high-resolution image synthesis

Reference 4

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Observation 917dba06-f192-474c-a46a-5000a07274ea · outbound

This paper cites Automatic lung segmentation in routine imaging is primarily a data diversity problem, not a methodology problem.

Explaining 3D Computed Tomography Classifiers with Counterfactuals Automatic lung segmentation in routine imaging is primarily a data diversity problem, not a methodology problem

Reference 5

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Observation d8fa3ffc-d855-4af3-b0da-8060ab83004e · outbound

This paper cites PleThora: Pleural effusion and thoracic cavity segmentations in diseased lungs for benchmarking chest CT processing pipelines.

Explaining 3D Computed Tomography Classifiers with Counterfactuals PleThora: Pleural effusion and thoracic cavity segmentations in diseased lungs for benchmarking chest CT processing pipelines

Reference 6

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Observation 79dab10d-1fb2-412b-a85a-1aba7459f920 · outbound

This paper cites Antoine, Mohamed H.

Explaining 3D Computed Tomography Classifiers with Counterfactuals Antoine, Mohamed H

Reference 7

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Source-reported events for the cited work

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Observation e2aac701-c30b-4e3a-853e-e726990bcd57 · outbound

This paper cites Counterfactual Image Synthesis for Discovery of Personalized Predictive Image Markers.

Explaining 3D Computed Tomography Classifiers with Counterfactuals Counterfactual Image Synthesis for Discovery of Personalized Predictive Image Markers

Reference 8

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Observation d3d35f49-8960-4d08-9645-edb31ccbcf51 · outbound

This paper cites CounteRGAN: Generating Realistic Counterfactuals with Residual Generative Adversarial Nets.

Explaining 3D Computed Tomography Classifiers with Counterfactuals CounteRGAN: Generating Realistic Counterfactuals with Residual Generative Adversarial Nets

Reference 9

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Observation 6a5747ed-e743-488a-858b-97501e9f2d6a · outbound

This paper cites PyTorch: An Imperative Style, High-Performance Deep Learning Library.

Explaining 3D Computed Tomography Classifiers with Counterfactuals PyTorch: An Imperative Style, High-Performance Deep Learning Library

Reference 10

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Observation 0ac9cec0-1778-43b0-9b1c-0f46ba238642 · outbound

This paper cites an unresolved cited work.

Explaining 3D Computed Tomography Classifiers with Counterfactuals Unresolved cited work

Reference 11

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Observation f7982f9e-8710-4183-93b5-edf5013c07a1 · outbound

This paper cites High Fidelity Image Counterfactuals with Probabilistic Causal Models.

Explaining 3D Computed Tomography Classifiers with Counterfactuals High Fidelity Image Counterfactuals with Probabilistic Causal Models

Reference 12

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verified exact
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Source-reported events for the cited work

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Observation 1ca62c50-a231-429d-b653-f96b87486dcf · outbound

This paper cites Seah, Jennifer S.N.

Explaining 3D Computed Tomography Classifiers with Counterfactuals Seah, Jennifer S.N

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 9ff8260e-6ecf-4187-9b7a-b4b11ab366ce · outbound

This paper cites Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization.

Explaining 3D Computed Tomography Classifiers with Counterfactuals Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization

Reference 14

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Observation 7e149507-40d9-420f-9aec-bd02bc7772e8 · outbound

This paper cites Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: the LUNA16 challenge.

Explaining 3D Computed Tomography Classifiers with Counterfactuals Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: the LUNA16 challenge

Reference 15

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Observation c442a045-9707-4b0f-9764-02a36ca37e78 · outbound

This paper cites Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps.

Explaining 3D Computed Tomography Classifiers with Counterfactuals Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps

Reference 16

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Observation 64fcaf9e-5f8d-43e9-a3e6-4c11050fc2f3 · outbound

This paper cites Explaining the black-box smoothly—A counterfactual approach.

Explaining 3D Computed Tomography Classifiers with Counterfactuals Explaining the black-box smoothly—A counterfactual approach

Reference 17

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Observation aea9e205-29f4-4101-b3d0-21894e6423bf · outbound

This paper cites Striving for Simplicity: The All Convolutional Net.

Explaining 3D Computed Tomography Classifiers with Counterfactuals Striving for Simplicity: The All Convolutional Net

Reference 18

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Observation 80f8982d-66cc-42b4-aa7a-bc8ef9962e8f · outbound

This paper cites A Review of Deep Learning Techniques for Lung Cancer Screening and Diagnosis Based on CT Images.

Explaining 3D Computed Tomography Classifiers with Counterfactuals A Review of Deep Learning Techniques for Lung Cancer Screening and Diagnosis Based on CT Images

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 514b1729-1814-4eaa-8d29-1e5791d6566f · outbound

This paper cites Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR.

Explaining 3D Computed Tomography Classifiers with Counterfactuals Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR

Reference 20

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Observation 53d61fc7-a966-45f2-a4e6-67806d29ab2a · outbound

This paper cites TotalSegmentator: robust segmentation of 104 anatomical structures in CT images.

Explaining 3D Computed Tomography Classifiers with Counterfactuals TotalSegmentator: robust segmentation of 104 anatomical structures in CT images

Reference 21

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Observation 6ffd5d86-8d01-41d7-bda6-b719004c8591 · outbound

This paper cites DeepLesion: Automated Deep Mining, Categorization and Detection of Significant Radiology Image Findings using Large-Scale Clinical Lesion Annotations.

Explaining 3D Computed Tomography Classifiers with Counterfactuals DeepLesion: Automated Deep Mining, Categorization and Detection of Significant Radiology Image Findings using Large-Scale Clinical Lesion Annotations

Reference 22

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Observation 21904715-e073-438c-8a5f-3d79c68f67be · outbound

This paper cites write newline.

Explaining 3D Computed Tomography Classifiers with Counterfactuals write newline

Reference 23

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Pith citing papers

Observation b80afd47-11ec-4198-9463-26c9247ba375 · inbound

CT-Agent: A Multimodal-LLM Agent for 3D CT Radiology Question Answering cites this paper.

CT-Agent: A Multimodal-LLM Agent for 3D CT Radiology Question Answering Explaining 3D Computed Tomography Classifiers with Counterfactuals

Reference 4

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