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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 2026-08-18T06:34:40.430872+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

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External citation measurements

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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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:35:08.880762Z digest=sha256:e6ee630ad038c449e6b7d90ba2bc7247ca798c5759642b26ee3ccdafe0f0efa7

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:59:57.759357Z digest=sha256:219b64def58842ec1757858a691bb35de918c8477eb69d11e2aebc461f48ae14

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T20:04:30.170229Z digest=sha256:900ca91b0a48113a01b264afbd038f4c79279e37e7e89e238d46be094a37f50b

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:54:27.453435Z digest=sha256:7df72ba97cc757d956aaee02425ba032ac7f6a3291247bcf63953eb2a4855c27

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

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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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-05-17T20:22:46.220021Z digest=sha256:c6034938a79ebee585a358a950f10a6bdcc326e407f87d0c9202f5513b514790

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.

source=pdf_text observed=2026-08-03T15:10:06.258737Z digest=sha256:35cd8f681b65e141a9b2300cc601d4e2eee5fa149336e53c9237aedb2850ec49

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

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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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-16T17:31:33.903063Z digest=sha256:890c97fac28ff80f4a2413e9dc8c3daa763e6864cb1326335c0d8c8eb07cfca7

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

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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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-14T22:14:41.083628Z digest=sha256:1de00752668b152c3d6483f4e7f4d73837b524f01c5d793fc9d8910346f360c9

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

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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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-10T16:25:38.430882Z digest=sha256:2804169fdbb6ebf8ebc129f637503d012159408ce8aef107419d8f809a932dc1

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

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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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-10T14:56:06.372343Z digest=sha256:a5ed44c70903d9821ca1882f068b75254837e9d71e103095c14968e692cb8ba5

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

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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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-10T08:16:33.482990Z digest=sha256:1f28f6981997569175eab55ddb5c2c808dee83bc80c4a4e716acc9a9ea6b01bf

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

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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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-10T05:37:27.060846Z digest=sha256:a4467b376552e8b0149f4fb40e042b26a67c2e181fc20017119f9e296fa17292

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

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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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-10T04:40:24.774730Z digest=sha256:965fff085af03cdd0ea94f8f92246c4084c0a6c85a6cbde0118448261f12ec58

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

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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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-10T05:16:45.854949Z digest=sha256:1c967769e5031cd5e2b6c8fdd1b60cb31a9d8aa27dfd66171cf35cea5f0d65ec

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

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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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-10T06:47:55.000226Z digest=sha256:86a654ab9a0567006c32bcdae3ca54ec005333431e33758e78e7f95bd96167a1

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

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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 2026-08-18T06:34:40.430872+00:00.

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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

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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 2026-08-18T06:34:40.430872+00:00.

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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

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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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-11T01:29:48.433348Z digest=sha256:159cf4c13cac239fd2126fd69f2a039e419f6c0c06fa2d45468857dd907b6a01

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

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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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-13T01:59:54.387041Z digest=sha256:2665a31b9560fd807d26f30c5b20df809d5064751a1be30adefc6c24dc82e2bf

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

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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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-20T23:14:10.235122Z digest=sha256:637c8409388664afac6ffbf7ee7af1d5516e6ae5d6c078c34f12814d4a6b57ea

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

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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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-14T20:13:38.290363Z digest=sha256:dfee6f693a5cd8fc1bfaf7b4aa2f4fc9e4d0f2f5ac39a857746d76ed78abdd11

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

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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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-14T19:36:27.412524Z digest=sha256:c3d8691e45274e35c38d15c9ba38bfae38461a53c540958aaf4765d705b226cb

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

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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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-20T05:37:23.299943Z digest=sha256:10f2facc4af20bfd2a9530c9d391c3edf2033d3f17a19defa70fafbb652b82f4

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-29T22:30:40.026693Z digest=sha256:2b56c121464564f93fc780c45169c5caf40e6acfc09d95dbb756653d2477adc0

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

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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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-29T18:26:10.873395Z digest=sha256:dadaa9c6e5a2007bf0f42db4365cfd8da99ecbafd485551d52a5e749568da2bd

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

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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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-28T17:37:46.185060Z digest=sha256:6d64a33c7474ec37f1a192865aaa120927bb2872a04416e57b83c6421f3bd206

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-28T01:54:34.167016Z digest=sha256:baaf5039540e9b8e17e3558f968dba6da46b3ef8bb0af1cfc1b0c6c0ce59322c

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

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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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-28T01:29:27.353291Z digest=sha256:c6f861edde159f40bf7de67bd96827b9b98aae69d5e1dfffc2951c51a42163ef

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-06-27T16:15:01.069458Z digest=sha256:3ac228a0b4c31d5ac7014ef66ce184c3d7244249b3f559dc1c167a8f5c6d952f

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-06-27T10:21:12.782864Z digest=sha256:826ff713eb1b0c0ed3d6a3a084c5c719ce04bda4ec9c32e5875578b271a88e8e

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

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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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-25T20:55:03.803170Z digest=sha256:2e7103e197e3e32b54ffff889091aaf89bc30f93c294ab3651ec4ae68d4d08cb

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-30T06:42:32.719983Z digest=sha256:7d184bd5d2e4b842830b089053420d37b0163de41e06335979be6ade43dd59ab

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-07-01T05:52:47.018861Z digest=sha256:fe9b84e005ccc425a5f1aff99af85b1094ce77e7ff1d3a8e96d10c5586caec83

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-07-02T02:15:14.226875Z digest=sha256:7e660f02c3d3a6d40c2b8085c7ae56d7a1876645f496e64f8fe5e22aac06e54f

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-07-08T20:07:52.847510Z digest=sha256:350d2fd9a775e9dec08fada58654978b322e76f50ea0def8f90350db6c77b810

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.

source=pdf_text observed=2026-08-01T18:20:42.754947Z digest=sha256:27d5409984015f57cefc46e79a028a3d63a25d15ae7951d5d784f1093a5aaf37

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.

source=pdf_text observed=2026-08-01T11:43:13.236874Z digest=sha256:8ca8ed1b3cfde0a9cb9edeb0a8802f6ace6596cb6fdafff7dd102e4bb2087f41

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.

source=pdf_text observed=2026-08-01T11:31:11.157800Z digest=sha256:ed5e5a79714e35b2ea17644a5d7c63653d50be4d6f269b0d20a267e9ce3b4e36

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.

source=pdf_text observed=2026-08-01T18:52:42.747676Z digest=sha256:c2f282db62d212d486fa8d2823283806511e62e74ad7fb3732286906b37d1fc1

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.

source=pdf_text observed=2026-07-30T15:42:49.087563Z digest=sha256:ff0c5145254208f16c3539b8581f287acd74c9053ecc03bf496554700b8ff97a

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.

source=pdf_text observed=2026-08-03T00:28:09.726170Z digest=sha256:ab04c3cef7e1f6fdef3cea895a0bd884a11363b2d6615dd234e6e2921deb78cb

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.

source=pdf_text observed=2026-08-03T15:00:00.522625Z digest=sha256:343741618470123b0a3d3f4104c5182227d7a418e4d777abd59c7087dcb027a8

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.

source=pdf_text observed=2026-08-03T11:49:55.880693Z digest=sha256:4ce71ada74cabfae786687181d6248609d7d7d46db1bfe8ac907c0b0856f11c1

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.

source=pdf_text observed=2026-08-06T11:14:00.900080Z digest=sha256:d01bb5ba0f3f353f83f608fa13d8054ca086673989378a76c3017ffc63d1aec8

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.

source=pdf_text observed=2026-08-11T13:44:05.012168Z digest=sha256:5bdbe1d1ab697315d51f051d57948121b20d19cddb4663450c8502778c1887f9

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.

source=pdf_text observed=2026-08-11T10:19:11.168984Z digest=sha256:d21dbff101603c3b9661e71da22ef178b3738a4b5f03efbbeb1c53b4fdf648ab

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.

source=pdf_text observed=2026-08-16T00:08:07.766296Z digest=sha256:28e1d15722782b19608749cad05744805c998954870862cba304efc8e9e45aef