Paper Citation Record · LEDGER

Revisiting MAE pre-training for 3D medical image segmentation

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2410.23132.

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

pith.paper-citation-record.v1
2410.23132 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:08:50.639302Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T05:30:23.456663Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

1
pith, observed 2026-08-10T05:30:23.456663Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation caf817f7-4799-408e-801a-f8227c6d77b6 · inbound

Precision ICU Resource Planning: A Multimodal Model for Brain Surgery Outcomes cites this paper.

Precision ICU Resource Planning: A Multimodal Model for Brain Surgery Outcomes Revisiting MAE pre-training for 3D medical image segmentation

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T11:06:22.062757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da93e52e-145d-4aad-b3f9-25678f83a464 · inbound

An OpenMind for 3D medical vision self-supervised learning cites this paper.

An OpenMind for 3D medical vision self-supervised learning Revisiting MAE pre-training for 3D medical image segmentation

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T05:53:40.820194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d4c2ec3-9845-48fd-814c-4340723e9d12 · inbound

Brain Imaging Foundation Models, Are We There Yet? A Systematic Review of Foundation Models for Brain Imaging and Biomedical Research cites this paper.

Brain Imaging Foundation Models, Are We There Yet? A Systematic Review of Foundation Models for Brain Imaging and Biomedical Research Revisiting MAE pre-training for 3D medical image segmentation

Reference 133

Resolution: unresolved; no resolver link, observed 2026-08-15T20:08:50.639302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4472b95-db8f-453e-a79f-c3db81ca88be · inbound

General Methods Make Great Domain-specific Foundation Models: A Case-study on Fetal Ultrasound cites this paper.

General Methods Make Great Domain-specific Foundation Models: A Case-study on Fetal Ultrasound Revisiting MAE pre-training for 3D medical image segmentation

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T23:11:30.157061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9ce6733d-47f1-4987-ab7d-fb0fba0523a0 · inbound

Benchmarking and Explaining Deep Learning Cortical Lesion MRI Segmentation in Multiple Sclerosis cites this paper.

Benchmarking and Explaining Deep Learning Cortical Lesion MRI Segmentation in Multiple Sclerosis Revisiting MAE pre-training for 3D medical image segmentation

Reference 45

Resolution: verified exact; local_arxiv, observed 2026-08-06T17:00:28.640006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.