Paper Citation Record · LEDGER

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI

As of 19 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2508.14133.

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

pith.paper-citation-record.v1
2508.14133 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T17:15:36.270733Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

30 of 30 outbound references displayed

verified exact0
verified fuzzy25
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c6135ab6-60f4-4529-89bd-10096e59a596 · outbound

This paper cites Expanding Criteria for Resectability of Colorectal Liver Metastases.

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI Expanding Criteria for Resectability of Colorectal Liver Metastases

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:15:36.504921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 585165f7-b70b-4cec-8f4c-d559d804316b · outbound

This paper cites Parenchymal sparing surgery brings treatment of colorectal liver metastases into the precision medicine era.

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI Parenchymal sparing surgery brings treatment of colorectal liver metastases into the precision medicine era

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:15:36.498037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0b961c10-3ea9-4fae-82f0-02531106f550 · outbound

This paper cites Using virtual 3D-models in surgical planning: workflow of an immersive virtual reality application in liver surgery.

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI Using virtual 3D-models in surgical planning: workflow of an immersive virtual reality application in liver surgery

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:15:36.489899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation cf83189f-025f-4918-9acc-5e701f040ca7 · outbound

This paper cites Consensus recommendations of three-dimensional visualization for diagnosis and management of liver diseases.

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI Consensus recommendations of three-dimensional visualization for diagnosis and management of liver diseases

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:15:36.482832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 453a0589-796c-407f-a49b-e13fc4c02a80 · outbound

This paper cites an unresolved cited work.

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-15T17:15:36.476092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 72499bac-fdbe-4d97-a7bd-0be382356d03 · outbound

This paper cites Ultrasound-based navigation for open liver surgery using active liver tracking.

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI Ultrasound-based navigation for open liver surgery using active liver tracking

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:15:36.468793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 89bcd19c-3ab1-4910-8f22-4cf4dbab7891 · outbound

This paper cites A surgical navigation system to aid the ablation of vanished colorectal liver metastases.

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI A surgical navigation system to aid the ablation of vanished colorectal liver metastases

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:15:36.461752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 586bfd56-a2f8-449e-98dd-19ddcf42b9d3 · outbound

This paper cites Deep learning for image-based liver analysis — A comprehensive review focusing on malignant lesions.

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI Deep learning for image-based liver analysis — A comprehensive review focusing on malignant lesions

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:15:36.454884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7f2972f2-a3fd-4317-9b8e-68885f9e2333 · outbound

This paper cites Deep learning techniques for liver and liver tumor segmentation: A review.

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI Deep learning techniques for liver and liver tumor segmentation: A review

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:15:36.447876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5f1a4bd6-d0b9-4fec-861c-0f9b14c92b6b · outbound

This paper cites an unresolved cited work.

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI Unresolved cited work

Reference 10

Resolution: unresolved; raw_fallback, observed 2026-08-15T17:15:36.440154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 82e9eb09-b597-43f4-bee6-b88fc8e0c8a4 · outbound

This paper cites an unresolved cited work.

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-15T17:15:36.432338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 81e0942a-bd47-4772-96ef-a732ceb39b8c · outbound

This paper cites Colorectal liver metastases: CT, MR imaging, and PET for diagnosis - Meta-analysis.

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI Colorectal liver metastases: CT, MR imaging, and PET for diagnosis - Meta-analysis

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:15:36.424464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a61a590c-6ac3-4405-92c9-f4bb69fe35cb · outbound

This paper cites Automated MRI liver segmentation for anatomical segmentation, liver volumetry, and the extraction of radiomics.

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI Automated MRI liver segmentation for anatomical segmentation, liver volumetry, and the extraction of radiomics

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:15:36.417251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8407aa0c-c2a6-4bbf-ae75-48fdb4fe1348 · outbound

This paper cites Automated segmentation of liver segment on portal venous phase MR images using a 3D convolutional neural network.

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI Automated segmentation of liver segment on portal venous phase MR images using a 3D convolutional neural network

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:15:36.408922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e40a4970-3f8e-4764-bfa0-9d3acd3d4ebb · outbound

This paper cites Deep Learning Framework for Liver Segmentation from T1-Weighted MRI Images.

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI Deep Learning Framework for Liver Segmentation from T1-Weighted MRI Images

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:15:36.401175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7b688fe0-401b-45a8-b2e5-73ec4a95dbb1 · outbound

This paper cites Training robust T1-weighted magnetic resonance imaging liver segmentation models using ensembles of datasets with different contrast protocols and liver disease etiologies.

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI Training robust T1-weighted magnetic resonance imaging liver segmentation models using ensembles of datasets with different contrast protocols and liver disease etiologies

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:15:36.393137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c69289e5-1193-439f-82b2-048d41815ad9 · outbound

This paper cites Convolutional neural network for automated segmentation of the liver and its vessels on non-contrast T1 vibe Dixon acquisitions.

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI Convolutional neural network for automated segmentation of the liver and its vessels on non-contrast T1 vibe Dixon acquisitions

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:15:36.385794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a12410c1-d86d-4584-bbd4-a7d148062f8d · outbound

This paper cites Automated 3D liver segmentation from hepatobiliary phase MRI for enhanced preoperative planning.

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI Automated 3D liver segmentation from hepatobiliary phase MRI for enhanced preoperative planning

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:15:36.378846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 94cd3860-7d34-4ea0-8481-3c773c574710 · outbound

This paper cites Liver vessel MRI image segmentation based on dual-path diffusion model.

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI Liver vessel MRI image segmentation based on dual-path diffusion model

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:15:36.371552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ddab29a1-d6dc-43bd-b18a-26bc766204f4 · outbound

This paper cites A workflow for automated segmentation of the liver surface, hepatic vasculature and biliary tree anatomy from multiphase MR images.

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI A workflow for automated segmentation of the liver surface, hepatic vasculature and biliary tree anatomy from multiphase MR images

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:15:36.363872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 25431772-3dc9-4cf6-acfb-5c0903e8633f · outbound

This paper cites 3D Slicer as an image computing platform for the Quantitative Imaging Network.

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI 3D Slicer as an image computing platform for the Quantitative Imaging Network

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-15T17:15:36.248030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd9fcdef-5da1-47c6-8707-2701c42db2cf · outbound

This paper cites nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation.

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:15:36.352469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 654599e9-c170-4f0b-aa64-65353f28ffbc · outbound

This paper cites Deep interactive thin object selection.

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI Deep interactive thin object selection

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:15:36.345456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e6e669b9-d624-42f7-9b3f-4991152f6b7c · outbound

This paper cites Full-resolution residual networks for semantic segmentation in street scenes.

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI Full-resolution residual networks for semantic segmentation in street scenes

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:15:36.331026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7811a11e-3114-4111-9b6c-58b8ab6c5597 · outbound

This paper cites CLDICE - A novel topology-preserving loss function for tubular structure segmentation.

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI CLDICE - A novel topology-preserving loss function for tubular structure segmentation

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:15:36.323308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b085026e-b23d-4d3e-b9ef-053204325d61 · outbound

This paper cites Optimization of hepatic vasculature segmentation from contrast-enhanced MRI, exploring two 3D Unet modifications and various loss functions.

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI Optimization of hepatic vasculature segmentation from contrast-enhanced MRI, exploring two 3D Unet modifications and various loss functions

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:15:36.316175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7f16c76e-bbbc-441e-a7f8-dbc1cc539eb1 · outbound

This paper cites Liver segmentation and metastases detection in MR images using convolutional neural networks.

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI Liver segmentation and metastases detection in MR images using convolutional neural networks

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:15:36.307842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 195c3975-41f6-4d59-b4b8-ab7ed62713ac · outbound

This paper cites Clinical Implementation of In-House Developed MR-Based Patient-Specific 3D Models of Liver Anatomy.

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI Clinical Implementation of In-House Developed MR-Based Patient-Specific 3D Models of Liver Anatomy

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:15:36.299622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 915d06ca-6bfd-4e14-9609-8bc5e7ddc9e7 · outbound

This paper cites Quantitative analysis of watershed geomorphology.

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI Quantitative analysis of watershed geomorphology

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:15:36.291899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 72ebca69-9953-48aa-aeb5-3580dd963ccb · outbound

This paper cites an unresolved cited work.

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI Unresolved cited work

Reference 2021

Resolution: unresolved; raw_fallback, observed 2026-08-15T17:15:36.338369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

No inbound Pith citation observations are available.