Paper Citation Record · LEDGER

MedSAM2-Anatomy: Training-Free Inference-Time Optimization for Musculoskeletal Segmentation

As of 7 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2608.00195.

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

pith.paper-citation-record.v1
2608.00195 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T00:41:16.366691Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

16 of 16 outbound references displayed

verified exact0
verified fuzzy0
unresolved16
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 42790c9c-4401-4757-b787-ecb374b713c7 · outbound

This paper cites U-net: Con- volutional networks for biomedical image segmentation,.

MedSAM2-Anatomy: Training-Free Inference-Time Optimization for Musculoskeletal Segmentation U-net: Con- volutional networks for biomedical image segmentation,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-04T00:41:14.746708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02dcc10f-687b-4516-89b4-c8b1486cf8ce · outbound

This paper cites nnu-net: a self-configuring method for deep learning-based biomedical image segmentation,.

MedSAM2-Anatomy: Training-Free Inference-Time Optimization for Musculoskeletal Segmentation nnu-net: a self-configuring method for deep learning-based biomedical image segmentation,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-04T00:41:14.815775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31537986-381b-4884-b813-823424cdc619 · outbound

This paper cites TotalSegmentator: Robust segmentation of 104 anatomic structures in CT images,.

MedSAM2-Anatomy: Training-Free Inference-Time Optimization for Musculoskeletal Segmentation TotalSegmentator: Robust segmentation of 104 anatomic structures in CT images,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-04T00:41:14.976485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 25a87cf8-82da-430b-8132-d15873c7d0de · outbound

This paper cites TotalSegmentator MRI: Robust sequence-independent segmentation of multiple anatomic structures in MRI,.

MedSAM2-Anatomy: Training-Free Inference-Time Optimization for Musculoskeletal Segmentation TotalSegmentator MRI: Robust sequence-independent segmentation of multiple anatomic structures in MRI,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-04T00:41:15.122673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aef52602-b65c-4134-a5fa-2af27a7ebf6a · outbound

This paper cites Segment Anything.

MedSAM2-Anatomy: Training-Free Inference-Time Optimization for Musculoskeletal Segmentation Segment Anything

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-04T00:41:15.332432Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c101501d-e2bd-4ae9-a50d-68af31e9f6a1 · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

MedSAM2-Anatomy: Training-Free Inference-Time Optimization for Musculoskeletal Segmentation SAM 2: Segment Anything in Images and Videos

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T00:41:15.535101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28a7cbbd-7bb9-464c-a9ae-b82d9760e71e · outbound

This paper cites Seg- ment anything in medical images,.

MedSAM2-Anatomy: Training-Free Inference-Time Optimization for Musculoskeletal Segmentation Seg- ment anything in medical images,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-04T00:41:15.696034Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6cb62f5-b832-4365-900b-ff900c638c7b · outbound

This paper cites Segment Anything in Medical Images and Videos: Benchmark and Deployment.

MedSAM2-Anatomy: Training-Free Inference-Time Optimization for Musculoskeletal Segmentation Segment Anything in Medical Images and Videos: Benchmark and Deployment

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-04T00:41:15.779105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c0d6e8f-45f1-4370-8556-ceeae469863c · outbound

This paper cites SIT-SAM: A semantic-integration trans- former that adapts the segment anything model to medical imaging,.

MedSAM2-Anatomy: Training-Free Inference-Time Optimization for Musculoskeletal Segmentation SIT-SAM: A semantic-integration trans- former that adapts the segment anything model to medical imaging,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-04T00:41:15.855416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f843e248-78a1-4aa4-a532-bb30b1e49d53 · outbound

This paper cites SegmentAnyBone: A Universal Model that Segments Any Bone at Any Location on MRI.

MedSAM2-Anatomy: Training-Free Inference-Time Optimization for Musculoskeletal Segmentation SegmentAnyBone: A Universal Model that Segments Any Bone at Any Location on MRI

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T00:41:15.939497Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 040b39dd-9746-4362-ade3-ec7bf2e5fa85 · outbound

This paper cites Foundation models for generalist medical artificial intelligence,.

MedSAM2-Anatomy: Training-Free Inference-Time Optimization for Musculoskeletal Segmentation Foundation models for generalist medical artificial intelligence,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-04T00:41:16.019650Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a3aeb96a-0a9d-4735-90b6-4b6c7f6be4fa · outbound

This paper cites Generalist mod- els in medical image segmentation: A survey and compar- ison,.

MedSAM2-Anatomy: Training-Free Inference-Time Optimization for Musculoskeletal Segmentation Generalist mod- els in medical image segmentation: A survey and compar- ison,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-04T00:41:16.072266Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation de94c243-5721-47cc-8d5c-19c3b7eb4ad7 · outbound

This paper cites nnInteractive: Redefining 3D Promptable Segmentation.

MedSAM2-Anatomy: Training-Free Inference-Time Optimization for Musculoskeletal Segmentation nnInteractive: Redefining 3D Promptable Segmentation

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T00:41:16.151395Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea113533-b00c-4ba2-9d02-974abe94fd98 · outbound

This paper cites A multiclass radiomics method-based WHO severity scale for improving COVID- 19 patient assessment and disease characterization from CT scans,.

MedSAM2-Anatomy: Training-Free Inference-Time Optimization for Musculoskeletal Segmentation A multiclass radiomics method-based WHO severity scale for improving COVID- 19 patient assessment and disease characterization from CT scans,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-04T00:41:16.226530Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f555ecfd-2abe-473b-8cc9-bf7d3f5d2bdf · outbound

This paper cites V oxTell: Free-text promptable universal 3D medical image segmen- tation,.

MedSAM2-Anatomy: Training-Free Inference-Time Optimization for Musculoskeletal Segmentation V oxTell: Free-text promptable universal 3D medical image segmen- tation,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-04T00:41:16.293357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c4ec2c6-9d1c-4dc5-b150-7d36ea942a2c · outbound

This paper cites MedGemma 1.5 Technical Report.

MedSAM2-Anatomy: Training-Free Inference-Time Optimization for Musculoskeletal Segmentation MedGemma 1.5 Technical Report

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-04T00:41:16.366691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.