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Paper Citation Record · LEDGER

Lung segmentation on chest x-ray images in patients with severe abnormal findings using deep learning

As of 20 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:1908.07704.

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

pith.paper-citation-record.v1
1908.07704 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T12:05:00.600581Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

22 of 22 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 871b45fb-b71d-48ca-b3d3-e7ea14273502 · outbound

This paper cites Dermatologist- level classification of skin cancer with deep neural networks.

Lung segmentation on chest x-ray images in patients with severe abnormal findings using deep learning Dermatologist- level classification of skin cancer with deep neural networks

Reference 1

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Observation bba8e921-d9d7-48ca-a450-a9faa0a76ffd · outbound

This paper cites Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs.

Lung segmentation on chest x-ray images in patients with severe abnormal findings using deep learning Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs

Reference 2

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation f21359d3-a760-4025-b4e5-c12846197725 · outbound

This paper cites an unresolved cited work.

Lung segmentation on chest x-ray images in patients with severe abnormal findings using deep learning Unresolved cited work

Reference 3

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Source-reported events for the cited work

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Observation 23b19246-d3d6-4829-8500-7817bfe55c87 · outbound

This paper cites Computer-aided diagnosis of liver tumors on computed tomography images.

Lung segmentation on chest x-ray images in patients with severe abnormal findings using deep learning Computer-aided diagnosis of liver tumors on computed tomography images

Reference 4

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verified fuzzy
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Source-reported events for the cited work

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Observation 85d28e4d-e9cd-40a9-874a-bc7cf3f67676 · outbound

This paper cites Pulmonary nodule detection in CT images with quantized convergence index filter.

Lung segmentation on chest x-ray images in patients with severe abnormal findings using deep learning Pulmonary nodule detection in CT images with quantized convergence index filter

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation f65e0e98-0d53-4a6d-835c-0415c7cf8050 · outbound

This paper cites Computer-aided detection of exophytic renal lesions on non-contrast CT images.

Lung segmentation on chest x-ray images in patients with severe abnormal findings using deep learning Computer-aided detection of exophytic renal lesions on non-contrast CT images

Reference 6

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Source-reported events for the cited work

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Observation d0f61b61-e240-4106-8ba5-3c715f709f08 · outbound

This paper cites Improved detection of lung nodules on chest radiographs using a commercial computer-aided diagnosis system.

Lung segmentation on chest x-ray images in patients with severe abnormal findings using deep learning Improved detection of lung nodules on chest radiographs using a commercial computer-aided diagnosis system

Reference 7

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 286ac155-82f6-4653-92f1-2ca5028f6e2d · outbound

This paper cites Deep Learning with Lung Segmentation and Bone Shadow Exclusion Techniques for Chest X-Ray Analysis of Lung Cancer.

Lung segmentation on chest x-ray images in patients with severe abnormal findings using deep learning Deep Learning with Lung Segmentation and Bone Shadow Exclusion Techniques for Chest X-Ray Analysis of Lung Cancer

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 3823c2c4-3078-43b6-b29f-ddcd81cf3287 · outbound

This paper cites Pulmonary nodules at chest CT: effect of computer-aided diagnosis on radiologists' detection performance.

Lung segmentation on chest x-ray images in patients with severe abnormal findings using deep learning Pulmonary nodules at chest CT: effect of computer-aided diagnosis on radiologists' detection performance

Reference 9

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation c7c9d601-9aae-4992-afe8-45dce42f8929 · outbound

This paper cites Comparison of Deep Learning Approaches for Multi-Label Chest X-Ray Classification.

Lung segmentation on chest x-ray images in patients with severe abnormal findings using deep learning Comparison of Deep Learning Approaches for Multi-Label Chest X-Ray Classification

Reference 10

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unresolved
no resolver link, observed 2026-08-14T12:05:00.546086Z

Source-reported events for the cited work

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Observation 5e346cc8-b50f-40b2-a2d7-1023fb58dffd · outbound

This paper cites Deep Learning Techniques for Medical Image Segmentation: Achievements and Challenges.

Lung segmentation on chest x-ray images in patients with severe abnormal findings using deep learning Deep Learning Techniques for Medical Image Segmentation: Achievements and Challenges

Reference 11

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verified exact
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Source-reported events for the cited work

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Observation 6def0789-6065-4f41-9652-e6851d7eb6d7 · outbound

This paper cites A fully automated algorithm for the segmentation of lung fields on digital chest radiographic images.

Lung segmentation on chest x-ray images in patients with severe abnormal findings using deep learning A fully automated algorithm for the segmentation of lung fields on digital chest radiographic images

Reference 12

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation ff757c4d-edfa-4ef5-926d-6afac34cf16d · outbound

This paper cites Segmentation of anatomical structures in chest radiographs using supervised methods: a comparative study on a public database.

Lung segmentation on chest x-ray images in patients with severe abnormal findings using deep learning Segmentation of anatomical structures in chest radiographs using supervised methods: a comparative study on a public database

Reference 13

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 0f344608-559f-47b7-82f0-49876662252e · outbound

This paper cites Lung segmentation in chest radiographs using anatomical atlases with nonrigid registration.

Lung segmentation on chest x-ray images in patients with severe abnormal findings using deep learning Lung segmentation in chest radiographs using anatomical atlases with nonrigid registration

Reference 14

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 8e9380d9-10ed-4223-9b24-1cfda9573aa1 · outbound

This paper cites U-net: convolutional networks for biomedical image segmentation.

Lung segmentation on chest x-ray images in patients with severe abnormal findings using deep learning U-net: convolutional networks for biomedical image segmentation

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 95805ec7-2408-49f2-af41-8edf047dd8ca · outbound

This paper cites an unresolved cited work.

Lung segmentation on chest x-ray images in patients with severe abnormal findings using deep learning Unresolved cited work

Reference 16

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Source-reported events for the cited work

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Observation 6316f466-a443-403c-bdd7-64948da843c5 · outbound

This paper cites Scalable Bayesian Optimization Using Deep Neural Networks.

Lung segmentation on chest x-ray images in patients with severe abnormal findings using deep learning Scalable Bayesian Optimization Using Deep Neural Networks

Reference 17

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Source-reported events for the cited work

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Observation e81ff41d-5517-4bbc-8fc2-cb5ea28d1e85 · outbound

This paper cites Computer-aided diagnosis of lung nodule using gradient tree boosting and Bayesian optimization.

Lung segmentation on chest x-ray images in patients with severe abnormal findings using deep learning Computer-aided diagnosis of lung nodule using gradient tree boosting and Bayesian optimization

Reference 18

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation b80a5e6d-ee04-4671-9c8e-0ad26f409b60 · outbound

This paper cites Two public chest X-ray datasets for computer-aided screening of pulmonary diseases.

Lung segmentation on chest x-ray images in patients with severe abnormal findings using deep learning Two public chest X-ray datasets for computer-aided screening of pulmonary diseases

Reference 19

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Source-reported events for the cited work

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Observation 5efa758d-28b9-460d-8f3b-6858ac5fa020 · outbound

This paper cites ChestX-ray8: Hospital-scale Chest X-ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases.

Lung segmentation on chest x-ray images in patients with severe abnormal findings using deep learning ChestX-ray8: Hospital-scale Chest X-ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases

Reference 20

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Source-reported events for the cited work

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Observation e99b0e27-368a-459f-afeb-6a52f6350391 · outbound

This paper cites https://github.com/imlab-uiip/lung-segmentation-2d (Last visited on 2019/06/29).

Lung segmentation on chest x-ray images in patients with severe abnormal findings using deep learning https://github.com/imlab-uiip/lung-segmentation-2d (Last visited on 2019/06/29)

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation f9250643-5b2e-4845-b22b-c23bd8a5370f · outbound

This paper cites Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift.

Lung segmentation on chest x-ray images in patients with severe abnormal findings using deep learning Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T12:05:00.676152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Pith citing papers

No inbound Pith citation observations are available.