Paper Citation Record · LEDGER

Automatic segmentation of kidney and liver tumors in CT images

As of 16 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 1 inbound Pith citation observation for arXiv:1908.01279.

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

pith.paper-citation-record.v1
1908.01279 v2

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T15:20:32.857299Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T15:20:32.857299Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-14T15:20:32.915342Z

Reference resolution

30 of 30 outbound references displayed

verified exact2
verified fuzzy20
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 15024490-d9ca-4a55-aba7-0bc1f8383690 · outbound

This paper cites Fast approxim ate energy minimiza- tion via graph cuts.

Automatic segmentation of kidney and liver tumors in CT images Fast approxim ate energy minimiza- tion via graph cuts

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:20:33.674843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 7d60c267-2b35-4ccb-8643-196399aa77b9 · outbound

This paper cites Schwartz.

Automatic segmentation of kidney and liver tumors in CT images Schwartz

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:20:33.651247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 6260c11d-22f6-431e-a1fc-b06b0f8973f6 · outbound

This paper cites A General Approach to Segmentation in CT Grayscale Images using Varia ble Neighborhood Search.

Automatic segmentation of kidney and liver tumors in CT images A General Approach to Segmentation in CT Grayscale Images using Varia ble Neighborhood Search

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:20:33.629927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 42121a94-27ab-4764-afaa-f9ad9e36c437 · outbound

This paper cites an unresolved cited work.

Automatic segmentation of kidney and liver tumors in CT images Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-14T15:20:33.602784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 492594d8-9827-4f20-b65e-451111b6b9c1 · outbound

This paper cites A Uniﬁed Level Set Framework Combining Hybrid Algorith ms for Liver and Liver Tumor Segmentation in CT Images.

Automatic segmentation of kidney and liver tumors in CT images A Uniﬁed Level Set Framework Combining Hybrid Algorith ms for Liver and Liver Tumor Segmentation in CT Images

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:20:33.581334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 0d83a8ed-660d-4b1d-b06e-4cc46eadddb0 · outbound

This paper cites Fully convolutional networks for semantic segmentation.

Automatic segmentation of kidney and liver tumors in CT images Fully convolutional networks for semantic segmentation

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:20:33.559676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e95b4864-407b-43c6-a086-5941c2156a9d · outbound

This paper cites Fully Convolutional Networks for Semantic Segmentation.

Automatic segmentation of kidney and liver tumors in CT images Fully Convolutional Networks for Semantic Segmentation

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:20:33.537429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 6ba06e2e-50b8-4523-a388-6c8c1af35f64 · outbound

This paper cites U-Ne t: Convolutional Net- works for Biomedical Image Segmentation.

Automatic segmentation of kidney and liver tumors in CT images U-Ne t: Convolutional Net- works for Biomedical Image Segmentation

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:20:33.503768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b487db76-80dc-4777-8331-07a95ef25027 · outbound

This paper cites Automatic Segment ation of Liver Tu- mor in CT Images with Deep Convolutional Neural Networks.

Automatic segmentation of kidney and liver tumors in CT images Automatic Segment ation of Liver Tu- mor in CT Images with Deep Convolutional Neural Networks

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:20:33.482755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d7b53d3b-4b37-40c0-9978-9defbe95cf8d · outbound

This paper cites Measures of the Amount of Ecologic Ass ociation Between Species.

Automatic segmentation of kidney and liver tumors in CT images Measures of the Amount of Ecologic Ass ociation Between Species

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:20:33.462020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 844cfef9-a1ee-4bc2-bf42-cc77b25827aa · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Automatic segmentation of kidney and liver tumors in CT images Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-14T15:20:32.690436Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 83412561-a15c-486e-a4c8-1a8c43fba849 · outbound

This paper cites 3D Deeply Supervised Network for Automatic Liver Segmentatio n from CT Volumes.

Automatic segmentation of kidney and liver tumors in CT images 3D Deeply Supervised Network for Automatic Liver Segmentatio n from CT Volumes

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:20:33.434290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 24d91d17-4729-45ca-98e9-b28f8109bf5b · outbound

This paper cites Aut omatic 3D liver location and segmentation via convolutional neural networ k and graph cut.

Automatic segmentation of kidney and liver tumors in CT images Aut omatic 3D liver location and segmentation via convolutional neural networ k and graph cut

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:20:33.405989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation df0d92a4-259e-4c3b-b9eb-9ef092b2a791 · outbound

This paper cites Automatic Liver and Tumor Segmentation of CT and MRI Volumes using Cascaded Fully Convolutional Neural Networks.

Automatic segmentation of kidney and liver tumors in CT images Automatic Liver and Tumor Segmentation of CT and MRI Volumes using Cascaded Fully Convolutional Neural Networks

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-14T15:20:32.712947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6eb9a874-a7b6-40d7-b1ab-016de474ee4b · outbound

This paper cites and others.

Automatic segmentation of kidney and liver tumors in CT images and others

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:20:33.380125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation cc7e901a-a723-4c47-a4f1-183fb6c0af1d · outbound

This paper cites Automat ic segmentation of liver tumors from multiphase contrast-enhanced CT images b ased on FCNs.

Automatic segmentation of kidney and liver tumors in CT images Automat ic segmentation of liver tumors from multiphase contrast-enhanced CT images b ased on FCNs

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:20:33.347178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 889582ac-88f3-477a-a450-1b10ddc14422 · outbound

This paper cites an unresolved cited work.

Automatic segmentation of kidney and liver tumors in CT images Unresolved cited work

Reference 17

Resolution: unresolved; raw_fallback, observed 2026-08-14T15:20:33.315726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f31aa391-f143-45ad-b5c8-1ea22afb1567 · outbound

This paper cites H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tu mor Segmentation From CT Volumes.

Automatic segmentation of kidney and liver tumors in CT images H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tu mor Segmentation From CT Volumes

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:20:33.278167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5956ac46-1736-4e7b-963c-65e3e4e21d53 · outbound

This paper cites an unresolved cited work.

Automatic segmentation of kidney and liver tumors in CT images Unresolved cited work

Reference 19

Resolution: unresolved; raw_fallback, observed 2026-08-14T15:20:33.253483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 585d696b-c5b9-4567-81df-fdd8ef6990f0 · outbound

This paper cites an unresolved cited work.

Automatic segmentation of kidney and liver tumors in CT images Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-08-14T15:20:33.232318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 11940065-3997-4e1d-b706-dd9f35a42cd2 · outbound

This paper cites RA-UNet: A hybrid deep attention-aware network to extract liver and tumor in CT scans.

Automatic segmentation of kidney and liver tumors in CT images RA-UNet: A hybrid deep attention-aware network to extract liver and tumor in CT scans

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-08-14T15:20:33.006239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 47443402-4bbc-486b-a07b-cc5775dd96f5 · outbound

This paper cites AHCNet: An Applica- tion of Attention Mechanism and Hybrid Connection for Liver Tumor Segmentation in CT Volumes.

Automatic segmentation of kidney and liver tumors in CT images AHCNet: An Applica- tion of Attention Mechanism and Hybrid Connection for Liver Tumor Segmentation in CT Volumes

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:20:33.208597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation ec31e7ab-f6ff-4345-8a7b-7e12e5b2bdb8 · outbound

This paper cites The KiTS19 Challenge Data: 300 Kidney Tumor Cases with Clinical Context, CT Semantic Segmentations, and Surgical Outcomes.

Automatic segmentation of kidney and liver tumors in CT images The KiTS19 Challenge Data: 300 Kidney Tumor Cases with Clinical Context, CT Semantic Segmentations, and Surgical Outcomes

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-14T15:20:32.787742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59416897-75d9-44e1-8aef-446379cbe85f · outbound

This paper cites LinkNet: Exploiting encoder repre- sentations for eﬃcient semantic segmentation.

Automatic segmentation of kidney and liver tumors in CT images LinkNet: Exploiting encoder repre- sentations for eﬃcient semantic segmentation

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:20:33.182072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 19d5a682-7255-4241-975b-2cd500be163b · outbound

This paper cites De ep Residual Learning for Image Recognition.

Automatic segmentation of kidney and liver tumors in CT images De ep Residual Learning for Image Recognition

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:20:33.160044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 821793f4-0adb-4fc9-b585-182cde26b3b1 · outbound

This paper cites Kalin in and Vladimir I.

Automatic segmentation of kidney and liver tumors in CT images Kalin in and Vladimir I

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:20:33.135997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a16a90f0-1cef-4fd3-bb17-8497e744b917 · outbound

This paper cites Automatic Liver Lesion Segmentation Using A Deep Convolutional Neural Network Method.

Automatic segmentation of kidney and liver tumors in CT images Automatic Liver Lesion Segmentation Using A Deep Convolutional Neural Network Method

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-14T15:20:32.832917Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cec8c180-c913-4dc1-9823-9e661786f54d · outbound

This paper cites Outer Wall Segmentation of Abdominal Aortic Aneurysm by Variable Neig hborhood Search Through Intensity and Gradient Spaces.

Automatic segmentation of kidney and liver tumors in CT images Outer Wall Segmentation of Abdominal Aortic Aneurysm by Variable Neig hborhood Search Through Intensity and Gradient Spaces

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:20:33.111220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 60dfa244-1f41-447c-a37c-c5aa1b63f728 · outbound

This paper cites Dynamic Regu lation of Level Set Parameters Using 3D Convolutional Neural Network for Liver Tumor Segmentation.

Automatic segmentation of kidney and liver tumors in CT images Dynamic Regu lation of Level Set Parameters Using 3D Convolutional Neural Network for Liver Tumor Segmentation

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:20:33.077959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9d65a063-ccd5-4496-a43b-7de61a14669a · outbound

This paper cites Automatic segmentation of kidney and liver tumors in CT images.

Automatic segmentation of kidney and liver tumors in CT images Automatic segmentation of kidney and liver tumors in CT images

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-08-14T15:20:32.928384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Pith citing papers

Observation 9d65a063-ccd5-4496-a43b-7de61a14669a · inbound