Paper Citation Record · LEDGER

MedSAM2: Segment Anything in 3D Medical Images and Videos

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 47 inbound Pith citation observations for arXiv:2504.03600.

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

pith.paper-citation-record.v1
2504.03600 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 47 of 47 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 47 of 47 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:08:07.766296Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-08T20:15:34.383554Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 738dca3a-03c3-4860-af58-168edf3adc7e · inbound

DrVD-Bench: Do Vision-Language Models Reason Like Human Doctors in Medical Image Diagnosis? cites this paper.

DrVD-Bench: Do Vision-Language Models Reason Like Human Doctors in Medical Image Diagnosis? MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:08.880762Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94dd62c6-cca6-40ab-b6c9-872a7ca4b214 · inbound

Towards Affordable Tumor Segmentation and Visualization for 3D Breast MRI Using SAM2 cites this paper.

Towards Affordable Tumor Segmentation and Visualization for 3D Breast MRI Using SAM2 MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T10:59:57.759357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 666cef99-1489-4293-bdc7-5e087d039133 · inbound

Live(r) Die: Predicting Survival in Colorectal Liver Metastasis cites this paper.

Live(r) Die: Predicting Survival in Colorectal Liver Metastasis MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:30.170229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a78a433c-5b63-4ddc-99b7-828e94b3a778 · inbound

ENSAM: an efficient foundation model for interactive segmentation of 3D medical images cites this paper.

ENSAM: an efficient foundation model for interactive segmentation of 3D medical images MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-15T15:54:27.453435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aee0cbd5-fbcb-41ad-8e80-5b04981a4de0 · inbound

SAM 3: Segment Anything with Concepts cites this paper.

SAM 3: Segment Anything with Concepts MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 88

Resolution: verified exact; arxiv_id, observed 2026-05-17T20:25:11.441824Z

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 86cfd2f3-cb85-4d60-98af-6b0b1e657f69 · inbound

Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation cites this paper.

Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T15:10:06.258737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33356c8c-56af-445f-9210-b21ee956e309 · inbound

IBISAgent: Reinforcing Pixel-Level Visual Reasoning in MLLMs for Universal Biomedical Object Referring and Segmentation cites this paper.

IBISAgent: Reinforcing Pixel-Level Visual Reasoning in MLLMs for Universal Biomedical Object Referring and Segmentation MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-16T17:33:10.069782Z

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 5b9ad8c8-eee7-4fe1-a9a7-61f04879e14c · inbound

BAAI Cardiac Agent: An intelligent multimodal agent for automated reasoning and diagnosis of cardiovascular diseases from cardiac magnetic resonance imaging cites this paper.

BAAI Cardiac Agent: An intelligent multimodal agent for automated reasoning and diagnosis of cardiovascular diseases from cardiac magnetic resonance imaging MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-14T22:18:04.668178Z

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 6888944a-6714-4736-8ce1-a08c45cb69aa · inbound

Delving Aleatoric Uncertainty in Medical Image Segmentation via Vision Foundation Models cites this paper.

Delving Aleatoric Uncertainty in Medical Image Segmentation via Vision Foundation Models MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-11T08:56:00.215664Z

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 c1d01a7f-ad43-41d8-abad-26d81ceaaeba · inbound

VERITAS: A Multi-Agent Co-Scientist for Verifiable Image-Derived Hypothesis Testing cites this paper.

VERITAS: A Multi-Agent Co-Scientist for Verifiable Image-Derived Hypothesis Testing MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:26:02.163132Z

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 b1fbe7ad-2473-4c38-9032-d0e5a304aa6f · inbound

Beyond a Single Frame: Multi-Frame Spatially Grounded Reasoning Across Volumetric MRI cites this paper.

Beyond a Single Frame: Multi-Frame Spatially Grounded Reasoning Across Volumetric MRI MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-10T08:17:37.012989Z

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 024ad08c-410c-4ca2-ac3a-c32b5830bea2 · inbound

SegTTA: Training-Free Test-Time Augmentation for Zero-Shot Medical Imaging Segmentation cites this paper.

SegTTA: Training-Free Test-Time Augmentation for Zero-Shot Medical Imaging Segmentation MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-10T05:41:02.343875Z

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 9bc998a6-5542-4744-a3ca-36d1e38c3904 · inbound

Align then Refine: Text-Guided 3D Prostate Lesion Segmentation cites this paper.

Align then Refine: Text-Guided 3D Prostate Lesion Segmentation MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-10T12:05:23.461729Z

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 fabd1002-aecf-456a-90bb-94372e3c2cd4 · inbound

CrossPan: A Comprehensive Benchmark for Cross-Sequence Pancreas MRI Segmentation and Generalization cites this paper.

CrossPan: A Comprehensive Benchmark for Cross-Sequence Pancreas MRI Segmentation and Generalization MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-10T09:28:39.343969Z

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 9080dbb9-4afc-45ba-b1b7-7acd700ed578 · inbound

SGP-SAM: Self-Gated Prompting for Transferring 3D Segment Anything Models to Lesion Segmentation cites this paper.

SGP-SAM: Self-Gated Prompting for Transferring 3D Segment Anything Models to Lesion Segmentation MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-10T06:51:46.303094Z

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 ca697586-aa6d-4e95-a047-fe25ac84a43d · inbound

Learning from Noisy Prompts: Saliency-Guided Prompt Distillation for Robust Segmentation with SAM cites this paper.

Learning from Noisy Prompts: Saliency-Guided Prompt Distillation for Robust Segmentation with SAM MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:31:14.669886Z

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 adf44b86-4ee1-4900-96da-1b121cb4f129 · inbound

ESICA: A Scalable Framework for Text-Guided 3D Medical Image Segmentation cites this paper.

ESICA: A Scalable Framework for Text-Guided 3D Medical Image Segmentation MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:46:43.204490Z

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 9ba63851-732d-4cce-99cb-380f41b034dc · inbound

AGA3DNet: Anatomy-Guided Gaussian Priors with Multi-view xLSTM for 3D Brain MRI Subtype Classification cites this paper.

AGA3DNet: Anatomy-Guided Gaussian Priors with Multi-view xLSTM for 3D Brain MRI Subtype Classification MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-11T01:45:51.773784Z

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 4c54072e-d1c6-40ab-a090-14f7c3304bd9 · inbound

ScribbleDose: Scribble-Guided Dose Prediction in Radiotherapy cites this paper.

ScribbleDose: Scribble-Guided Dose Prediction in Radiotherapy MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 10

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T02:02:06.391899Z

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 12e19c12-aa36-47bf-bcb2-ad2e416f14e0 · inbound

ScribbleDose: Scribble-Guided Dose Prediction in Radiotherapy cites this paper.

ScribbleDose: Scribble-Guided Dose Prediction in Radiotherapy MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-20T23:14:11.957585Z

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 37f7f997-8a35-41ae-b218-c4a2abb939b6 · inbound

MedCore: Boundary-Preserving Medical Core Pruning for MedSAM cites this paper.

MedCore: Boundary-Preserving Medical Core Pruning for MedSAM MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:19:28.488926Z

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 72fb8d21-a517-4455-ac33-a52264395833 · inbound

VoxCor: Training-Free Volumetric Features for Multimodal Voxel Correspondence cites this paper.

VoxCor: Training-Free Volumetric Features for Multimodal Voxel Correspondence MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-14T19:37:52.187976Z

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 743fa12b-e920-458b-917c-407a60e9cfb2 · inbound

Rethinking Visual Attribution for Chest X-ray Reasoning in Large Vision Language Models cites this paper.

Rethinking Visual Attribution for Chest X-ray Reasoning in Large Vision Language Models MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-20T05:38:05.053768Z

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 331d89ce-a3a4-46df-88b8-ecd6634e2e83 · inbound

EchoPilot: Training-Free Ultrasound Video Segmentation via Scale-Space Semantic Prompting and Reliability-Gated Memory cites this paper.

EchoPilot: Training-Free Ultrasound Video Segmentation via Scale-Space Semantic Prompting and Reliability-Gated Memory MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 15

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T22:34:01.515997Z

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 7565d2cd-b6a7-41ee-a155-b2033aef5626 · inbound

MedVol-R1: Reward-Driven Evidence Grounding for Volumetric Reasoning Segmentation cites this paper.

MedVol-R1: Reward-Driven Evidence Grounding for Volumetric Reasoning Segmentation MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 12

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T18:33:50.902756Z

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 5851c64f-a95c-4cdf-b85c-6ecb2fac1129 · inbound

SWARD: Stochastic Window-Attention-Based Relational Distillation for Cross-Architectural Semantic Segmentation cites this paper.

SWARD: Stochastic Window-Attention-Based Relational Distillation for Cross-Architectural Semantic Segmentation MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-07-01T20:56:13.940510Z

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 2d562782-af29-425e-878a-9f6c16d48f97 · inbound

MS-DKC: A Dataset Knowledge Card Framework for Designing and Adapting Medical Image Segmentation Models cites this paper.

MS-DKC: A Dataset Knowledge Card Framework for Designing and Adapting Medical Image Segmentation Models MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 44

Resolution: malformed identifier; arxiv_id, observed 2026-07-02T12:46:56.572466Z

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 463fd881-b136-44d0-aa88-c6de070a5de5 · inbound

MedSIGHT: Towards Grounded Visual Comprehension in Medical Large Vision-Language Models cites this paper.

MedSIGHT: Towards Grounded Visual Comprehension in Medical Large Vision-Language Models MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-07-02T13:16:58.482778Z

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 5c815773-c89d-4167-917e-1382cc6b4237 · inbound

BenSyc: Benchmarking Conversational Sycophancy and Human Alignment in LLMs for Bengali Contexts cites this paper.

BenSyc: Benchmarking Conversational Sycophancy and Human Alignment in LLMs for Bengali Contexts MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 28

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T01:47:32.011678Z

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 9bb396b4-e986-47be-81e9-eab4f7e872f2 · inbound

UniReason-Med: A Shared Grounded Reasoning Interface for 2D-to-3D Transfer in Medical VQA cites this paper.

UniReason-Med: A Shared Grounded Reasoning Interface for 2D-to-3D Transfer in Medical VQA MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 236

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T09:47:59.369675Z

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 e10b7e0b-13ad-4c27-8d86-40f4a474ba63 · inbound

MRI2Rep: Autoregressive Structured Report Generation for 3D Liver MRI cites this paper.

MRI2Rep: Autoregressive Structured Report Generation for 3D Liver MRI MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 22

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T20:00:08.152920Z

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 b5d5d899-e9b6-4f28-8d23-54e3e0266bee · inbound

PGE-SAM: Prompt-Guided Feature Enhancement for Interactive Segmentation under Degradation cites this paper.

PGE-SAM: Prompt-Guided Feature Enhancement for Interactive Segmentation under Degradation MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 44

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T06:44:18.775063Z

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 74011435-a521-41b5-9fc4-6c4b845dc81e · inbound

Towards Voxel Spacing Consistency for Medical Image Segmentation cites this paper.

Towards Voxel Spacing Consistency for Medical Image Segmentation MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-07-01T10:05:41.106188Z

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 f6d8f59b-3428-4d49-97cc-c1d90165bc94 · inbound

Closed-loop coupling of personalised and foundation models for real-time treatment guidance with MRI cites this paper.

Closed-loop coupling of personalised and foundation models for real-time treatment guidance with MRI MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-07-02T02:16:25.689080Z

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 09147297-8b8c-41a2-be00-1269241d41e6 · inbound

OBBSeg: Irregular Lesion Segmentation under Oriented Bounding Box Annotations cites this paper.

OBBSeg: Irregular Lesion Segmentation under Oriented Bounding Box Annotations MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 26

Resolution: metadata mismatch; local_arxiv, observed 2026-07-08T20:15:34.384917Z

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 a0eb3acd-a51d-4379-bf15-d81ade15a3ee · inbound

MIS-HCC: Hierarchical Channel Clustering for Efficient Medical Image Segmentation cites this paper.

MIS-HCC: Hierarchical Channel Clustering for Efficient Medical Image Segmentation MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-01T18:20:42.754947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c415da8-2190-476d-8ca4-6c3d95c9e9b7 · inbound

Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2 cites this paper.

Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2 MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-01T11:43:13.236874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1da2d8fd-6d47-4647-83cb-1539456ce929 · inbound

Robust Activation Map Rectification for Weakly Supervised Volumetric Segmentation: Temporal Coherence as a Free Lunch cites this paper.

Robust Activation Map Rectification for Weakly Supervised Volumetric Segmentation: Temporal Coherence as a Free Lunch MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-01T11:31:11.157800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9b557d1-c48e-42c0-9afc-3a7119046b28 · inbound

Histopathological Spectrum-Guided Prostate Stratification via Segmentation-Assisted Diagnostic Transformer cites this paper.

Histopathological Spectrum-Guided Prostate Stratification via Segmentation-Assisted Diagnostic Transformer MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-01T18:52:42.747676Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ec8f99a-d2ee-4c2d-96f2-75ae918c1a99 · inbound

Parameter-Efficient Adaptation of SAM3 for Prompt-Driven Surgical Concept Segmentation cites this paper.

Parameter-Efficient Adaptation of SAM3 for Prompt-Driven Surgical Concept Segmentation MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-30T15:42:49.087563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e73781d4-7af3-4cfc-9e3b-0e4fd466fa56 · inbound

Do Medical Foundation Models Generalize on the African Brain? cites this paper.

Do Medical Foundation Models Generalize on the African Brain? MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T00:28:09.726170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85a4323a-7bff-498f-8223-092666ad29fe · inbound

SAM+D: Parameter-Efficient Dimensional Lifting of SAM-Family Models via Depth-Routed LoRA and Depth Shifting cites this paper.

SAM+D: Parameter-Efficient Dimensional Lifting of SAM-Family Models via Depth-Routed LoRA and Depth Shifting MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-03T15:00:00.522625Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e68bf7d-3db7-4c17-ba7c-f071f4f76479 · inbound

UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation cites this paper.

UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T11:49:55.880693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 12727be3-fef7-4656-a7b0-cde047f12736 · inbound

ArtAnno: Annotating Implicit Semantics in Artworks through LLM Agent-Driven Bidirectional Human-AI Augmentation cites this paper.

ArtAnno: Annotating Implicit Semantics in Artworks through LLM Agent-Driven Bidirectional Human-AI Augmentation MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-06T11:14:00.900080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c929d3f3-f060-41dc-b134-5fcb118bdec4 · inbound

NeuroRefiner: Morphology-Aware Multi-Agent Refinement for 3D Fluorescence Microscopy Neuron Segmentation cites this paper.

NeuroRefiner: Morphology-Aware Multi-Agent Refinement for 3D Fluorescence Microscopy Neuron Segmentation MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T13:44:05.012168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2aec99d-aeeb-4578-a628-46a8b4f875c3 · inbound

MedPixel: A Unified Pixel-Language Model for Medical Reasoning and Segmentation cites this paper.

MedPixel: A Unified Pixel-Language Model for Medical Reasoning and Segmentation MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T10:19:11.168984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17a58eee-d953-4aac-ad04-c3d367ef5c61 · inbound

Auditable agentic AI for evidence-grounded thyroid ultrasound diagnosis and reporting cites this paper.

Auditable agentic AI for evidence-grounded thyroid ultrasound diagnosis and reporting MedSAM2: Segment Anything in 3D Medical Images and Videos

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-16T00:08:07.766296Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.