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Paper Citation Record · LEDGER

Medical SAM 2: Segment medical images as video via Segment Anything Model 2

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 48 inbound Pith citation observations for arXiv:2408.00874.

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

pith.paper-citation-record.v1
2408.00874 v2

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measured 0 of 0 reference resolution

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Source: paper_references, paper_reference_links

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 48 of 48 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T22:32:36.945058Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T13:09:51.350634Z

Reference resolution

0 of 0 outbound references displayed

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 0aa23061-ed4e-424e-832d-363c942e3544 · inbound

On Efficient Variants of Segment Anything Model: A Survey cites this paper.

On Efficient Variants of Segment Anything Model: A Survey Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 96

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arxiv_id, observed 2026-05-23T19:43:23.376662Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-23T19:42:24.122342Z digest=sha256:0ab9729ed2c7aeba190ba363fb0670d9364f298b28a0b70073b309fa5c8adb28

Observation 151a27e7-94a2-42b7-ac96-90453ebec9ff · inbound

Multimodal HIE Lesion Segmentation in Neonates: A Comparative Study of Loss Functions cites this paper.

Multimodal HIE Lesion Segmentation in Neonates: A Comparative Study of Loss Functions Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 2024

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Unavailable: canonical work link unavailable.

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Observation 3060988f-c30a-422c-8d29-1d44b32fd8e1 · inbound

Segment Any-Quality Images with Generative Latent Space Enhancement cites this paper.

Segment Any-Quality Images with Generative Latent Space Enhancement Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 75

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arxiv_id, observed 2026-05-22T23:47:15.682881Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation b28fe696-307a-46f6-99c5-03b5a5977beb · inbound

Zero-Shot Gaze-based Volumetric Medical Image Segmentation cites this paper.

Zero-Shot Gaze-based Volumetric Medical Image Segmentation Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 3

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no resolver link, observed 2026-08-07T15:24:30.634508Z

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source=pdf_text observed=2026-08-07T15:24:30.634508Z digest=sha256:95150d3f7c6b51f02831ce6118634db5ac71ffcf0b60178edaa1e33aea55f08d

Observation a0e7bfcc-444b-442b-95f3-f8d954c20348 · inbound

iDPA: Instance Decoupled Prompt Attention for Incremental Medical Object Detection cites this paper.

iDPA: Instance Decoupled Prompt Attention for Incremental Medical Object Detection Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 60

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no resolver link, observed 2026-08-07T12:09:57.443836Z

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source=arxiv_source observed=2026-08-07T12:09:57.443836Z digest=sha256:d9c3277138adb5091f33f205c6d03db764cad17cea4b20d9463e0793b8042da3

Observation d6722ea7-d27d-4d4b-a968-83bc9046d004 · inbound

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost cites this paper.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 58

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no resolver link, observed 2026-08-07T11:52:49.909797Z

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Unavailable: canonical work link unavailable.

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Observation 4455d35e-f1b9-413a-a42e-4be7e47c63f0 · inbound

SSS: Semi-Supervised SAM-2 with Efficient Prompting for Medical Imaging Segmentation cites this paper.

SSS: Semi-Supervised SAM-2 with Efficient Prompting for Medical Imaging Segmentation Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 58

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no resolver link, observed 2026-08-07T05:03:38.658134Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:03:38.658134Z digest=sha256:80c320e3605dd0f8f0876106dc9f23717c1cb7dd49b04e3ecf6accb7f8744d63

Observation 88793101-f121-4905-971b-1daf21007165 · inbound

SafeClick: Error-Tolerant Interactive Segmentation of Any Medical Volumes via Hierarchical Expert Consensus cites this paper.

SafeClick: Error-Tolerant Interactive Segmentation of Any Medical Volumes via Hierarchical Expert Consensus Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 7

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no resolver link, observed 2026-08-06T23:21:36.815334Z

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Unavailable: canonical work link unavailable.

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Observation fa43311a-a11b-46ba-9c8b-81eefc2bb459 · inbound

CRISP-SAM2: SAM2 with Cross-Modal Interaction and Semantic Prompting for Multi-Organ Segmentation cites this paper.

CRISP-SAM2: SAM2 with Cross-Modal Interaction and Semantic Prompting for Multi-Organ Segmentation Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 129

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no resolver link, observed 2026-08-06T21:54:43.713908Z

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Observation f8096e88-5eb6-4c6f-ae4d-cd2a1197d7c6 · inbound

SAMed-2: Selective Memory Enhanced Medical Segment Anything Model cites this paper.

SAMed-2: Selective Memory Enhanced Medical Segment Anything Model Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 23

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Observation 897196e1-dddb-44dc-aea0-0ece90c87b88 · inbound

Dual Semantic-Aware Network for Noise Suppressed Ultrasound Video Segmentation cites this paper.

Dual Semantic-Aware Network for Noise Suppressed Ultrasound Video Segmentation Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 33

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no resolver link, observed 2026-08-06T18:45:43.704791Z

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Unavailable: canonical work link unavailable.

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Observation 4cb9b5c1-eafc-4a10-8fda-832773febfc4 · inbound

RAPS-3D: Efficient interactive segmentation for 3D radiological imaging cites this paper.

RAPS-3D: Efficient interactive segmentation for 3D radiological imaging Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 13

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no resolver link, observed 2026-08-06T18:38:40.625326Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:38:40.625326Z digest=sha256:00c59588cb984fbd56e1082094ed603716972d2fe5affddcc0f832a1854504ea

Observation 91e69941-6e95-467c-9d8c-6c6d3b3fb62c · inbound

F3-Net: Foundation Model for Full Abnormality Segmentation of Medical Images with Flexible Input Modality Requirement cites this paper.

F3-Net: Foundation Model for Full Abnormality Segmentation of Medical Images with Flexible Input Modality Requirement Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 7

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no resolver link, observed 2026-08-06T18:24:51.681829Z

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Unavailable: canonical work link unavailable.

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Observation 640eb48c-7d40-456e-98a3-1a8c94ae07d0 · inbound

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation cites this paper.

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 29

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no resolver link, observed 2026-08-06T17:58:48.140418Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:58:48.140418Z digest=sha256:850673a2f679ad07d7f7c70f51bba93cb14316ba234af07dfdb7b041eaab5e2a

Observation e98db074-677c-42cc-b852-c7e987d9c7e0 · inbound

Depthwise-Dilated Convolutional Adapters for Medical Object Tracking and Segmentation Using the Segment Anything Model 2 cites this paper.

Depthwise-Dilated Convolutional Adapters for Medical Object Tracking and Segmentation Using the Segment Anything Model 2 Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 7

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no resolver link, observed 2026-08-06T15:56:39.022143Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:56:39.022143Z digest=sha256:b2d2e773c99189a869b0de3b52ce91ef78a816ab03ef820e606e8ecbe4f06132

Observation 382c46cd-c1f0-47fa-a85c-d6a4ff518cc7 · inbound

HRVVS: A High-resolution Video Vasculature Segmentation Network via Hierarchical Autoregressive Residual Priors cites this paper.

HRVVS: A High-resolution Video Vasculature Segmentation Network via Hierarchical Autoregressive Residual Priors Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 35

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no resolver link, observed 2026-08-06T11:38:37.806083Z

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Unavailable: canonical work link unavailable.

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Observation a225cade-e78e-4ce3-a962-765534c497ac · 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 Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 26

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no resolver link, observed 2026-08-06T10:59:57.783157Z

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Unavailable: canonical work link unavailable.

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Observation 1c79325a-f042-4322-803a-e76d2311ed76 · inbound

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

Live(r) Die: Predicting Survival in Colorectal Liver Metastasis Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 70

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malformed identifier
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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T20:04:30.188226Z digest=sha256:b75c8e0648056811507ca463d46c76006f82be03aada777903cde0cc203d1ede

Observation 7e709095-40c2-41b6-a381-695799356432 · inbound

Organoid Tracker: A SAM2-Powered Platform for Zero-shot Cyst Analysis in Human Kidney Organoid Videos cites this paper.

Organoid Tracker: A SAM2-Powered Platform for Zero-shot Cyst Analysis in Human Kidney Organoid Videos Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 11

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no resolver link, observed 2026-08-04T17:10:49.056775Z

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Unavailable: canonical work link unavailable.

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Observation 8957482f-d9a1-407f-a997-3472f4c46f25 · inbound

Label-Efficient Cross-Modality Generalization for Liver Segmentation in Multi-Phase MRI cites this paper.

Label-Efficient Cross-Modality Generalization for Liver Segmentation in Multi-Phase MRI Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 22

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verified exact
arxiv_id, observed 2026-05-18T10:31:14.819118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 4a9d89f9-8e8e-4fe4-a587-1c65f9989245 · inbound

RASALoRE: Region Aware Spatial Attention with Location-based Random Embeddings for Weakly Supervised Anomaly Detection in Brain MRI Scans cites this paper.

RASALoRE: Region Aware Spatial Attention with Location-based Random Embeddings for Weakly Supervised Anomaly Detection in Brain MRI Scans Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 40

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arxiv_id, observed 2026-05-18T09:11:09.890968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-18T09:07:19.408341Z digest=sha256:fff551f529a8936f0851556abf8c70ce55da932f4758b3397bc7a60ffbec7a4c

Observation a01a10f0-7821-4ff2-8519-c9d9a537c6ca · inbound

Memory-SAM: Human-Prompt-Free Tongue Segmentation via Retrieval-to-Prompt cites this paper.

Memory-SAM: Human-Prompt-Free Tongue Segmentation via Retrieval-to-Prompt Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 11

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arxiv_id, observed 2026-05-18T06:05:57.442113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-18T06:03:45.684267Z digest=sha256:9278b95a4fefd6914009f7030d570952631a30008fe705c63a6240cc341129f9

Observation accf13e2-f442-4295-acbb-c2e0912b6ded · inbound

Memory-SAM: Human-Prompt-Free Tongue Segmentation via Retrieval-to-Prompt cites this paper.

Memory-SAM: Human-Prompt-Free Tongue Segmentation via Retrieval-to-Prompt Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 11

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no resolver link, observed 2026-08-04T09:21:21.122211Z

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Unavailable: canonical work link unavailable.

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Observation 9e7a47d7-c2e7-4e64-92fc-b8d33693db6c · inbound

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking cites this paper.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 55

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no resolver link, observed 2026-08-03T21:12:07.539556Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T21:12:07.539556Z digest=sha256:54f46fefbd78d633392b19dd70fe3ff9344f4e1e7e58281ee16112ed5815914a

Observation 29e1e0d9-268a-40fd-b55e-3c67b59422a2 · inbound

SAM-MI: A Mask-Injected Framework for Enhancing Open-Vocabulary Semantic Segmentation with SAM cites this paper.

SAM-MI: A Mask-Injected Framework for Enhancing Open-Vocabulary Semantic Segmentation with SAM Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 35

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no resolver link, observed 2026-08-03T20:27:24.765165Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T20:27:24.765165Z digest=sha256:fcefe92883abe341a573d692ce809871df3da37863e22a35cd9de1bddd7724cb

Observation 5dcfe04c-6e06-4b7e-b968-fd7c060d4064 · inbound

Backdoor Attacks on Prompt-Driven Video Segmentation Foundation Models cites this paper.

Backdoor Attacks on Prompt-Driven Video Segmentation Foundation Models Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 69

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metadata mismatch
arxiv_id, observed 2026-05-16T19:11:11.682101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-16T19:08:37.460895Z digest=sha256:7e06dd0ba0154225e830b5ef77be0c5bc5eb2516615528e1bc3dcbbab2dbdae8

Observation 41a800b1-c0a0-4cbc-942c-781549f003f6 · inbound

Towards Any-Quality Image Segmentation via Generative and Adaptive Latent Space Enhancement cites this paper.

Towards Any-Quality Image Segmentation via Generative and Adaptive Latent Space Enhancement Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 74

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arxiv_id, observed 2026-05-16T18:13:13.222183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 4c8a7fea-1bb0-4640-abf4-aec798455829 · inbound

DivAS: Interactive 3D Segmentation by Depth-Weighted Voxel Aggregation cites this paper.

DivAS: Interactive 3D Segmentation by Depth-Weighted Voxel Aggregation Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 32

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no resolver link, observed 2026-08-03T11:58:53.399042Z

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Unavailable: canonical work link unavailable.

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Observation 887bbd4d-ebca-4aad-9fca-91cdcae56010 · inbound

Seeing Through the Tool: A Controlled Benchmark for Occlusion Robustness in Foundation Segmentation Models cites this paper.

Seeing Through the Tool: A Controlled Benchmark for Occlusion Robustness in Foundation Segmentation Models Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 29

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verified exact
arxiv_id, observed 2026-05-11T08:56:01.492563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T16:24:52.056950Z digest=sha256:78c2e2d870740153873d4f4eb497b508edd874c6215e5c59b234cf25a5d8aa21

Observation 6edb560e-4360-409b-9d33-480aeaf1bcb2 · 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 Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 8

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arxiv_id, observed 2026-05-11T11:26:02.170892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 494d310f-fd33-481a-a2ad-90737824d83e · 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 Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 5

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verified exact
arxiv_id, observed 2026-05-10T06:51:46.300385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T06:47:55.000226Z digest=sha256:5981be5f53ed8d8c113098023c7a1ca6a9f39b79206458e4d37e6217ea025dc4

Observation e6247e1c-bb78-4c84-a1d7-2abd7474d37f · inbound

A Real-time Scale-robust Network for Glottis Segmentation in Nasal Transnasal Intubation cites this paper.

A Real-time Scale-robust Network for Glottis Segmentation in Nasal Transnasal Intubation Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 57

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metadata mismatch
arxiv_id, observed 2026-05-12T09:36:26.098020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-07T10:28:59.595352Z digest=sha256:536cabb052bfa6b4072b97f1efb3fabaebd493c5d39d7888d6f3b563eb0c06a6

Observation 205b2229-4deb-48ef-8ca6-925159186940 · inbound

CAR-SAM: Cross-Attention Reconstruction for Post-Training Quantization of the Segment Anything Model cites this paper.

CAR-SAM: Cross-Attention Reconstruction for Post-Training Quantization of the Segment Anything Model Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 29

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verified exact
arxiv_id, observed 2026-05-19T21:32:47.889669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-19T21:30:10.628872Z digest=sha256:112078c27a5925033e83faf93806f0403ce36c0febf41704f14732e0c3ff9a9f

Observation 12fed2ef-009f-4a89-be88-60e2af133d79 · inbound

Speech-Guided Multimodal Learning for Vocal Tract Segmentation in Real-Time MRI cites this paper.

Speech-Guided Multimodal Learning for Vocal Tract Segmentation in Real-Time MRI Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 34

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verified exact
arxiv_id, observed 2026-05-20T11:43:15.185129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-20T11:40:19.027987Z digest=sha256:33c3c97e55a9e5422178783df12c6ce99807380b69882738b7bc8f3e78562475

Observation 68203bbf-f793-41bb-8366-d53be6d4d761 · inbound

Enhancing MedSAM with a Lightweight Box Predictor for Medical Image Segmentation cites this paper.

Enhancing MedSAM with a Lightweight Box Predictor for Medical Image Segmentation Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 23

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T06:56:44.601734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-28T07:16:51.935517Z digest=sha256:9ef72c75f5d3f7bad5844e59422bb78385406e49b59941170083ef7231c45e9c

Observation 6a711d24-e5e3-4b61-8556-53978bd2dc38 · inbound

Enhancing MedSAM with a Lightweight Box Predictor for Medical Image Segmentation cites this paper.

Enhancing MedSAM with a Lightweight Box Predictor for Medical Image Segmentation Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-02T12:27:07.644486Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T12:27:07.644486Z digest=sha256:acf926fc4028c755166f629fc453fb6fd80565523f76b9fa4d8cdadac926e405

Observation d131dcd4-cc8e-4f55-9688-daf82aac4653 · inbound

Parameter-Efficient Adaptation of SAM 3 for Automated ITV Generation from 4DCT Images cites this paper.

Parameter-Efficient Adaptation of SAM 3 for Automated ITV Generation from 4DCT Images Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-07-03T17:08:43.574338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-27T04:33:53.783148Z digest=sha256:2c54adf93e19dcca78272f7bfc643ea2752291a50235d70bd92a4b334716d9e6

Observation f75bd0c7-9831-41d9-8a9b-738769e80d94 · inbound

Geometry-Consistent Endoscopic Representations for Image-Guided Navigation via Structured Foundation Model Adaptation cites this paper.

Geometry-Consistent Endoscopic Representations for Image-Guided Navigation via Structured Foundation Model Adaptation Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 7

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T18:18:49.909235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-27T03:12:46.606412Z digest=sha256:134f274c4c4428d7a3da6ed51a83335a99fe32ff236f363e42c59bdd89299a20

Observation ac896975-0936-412a-9395-6cd5676f35ac · inbound

Human and AI collaboration for pulmonary nodule segmentation cites this paper.

Human and AI collaboration for pulmonary nodule segmentation Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-07-04T08:59:42.194066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-26T10:48:08.928264Z digest=sha256:3b607054b58ffc282dc91fb99d1fdf9650ae895acc76c70bac2d3a4a1619dc78

Observation 6e02af7f-ca04-4e2c-8378-c8bb7cbfc527 · inbound

Tractography-Driven Synthetic Data Generation for Fiber Bundle Segmentation in Tracer Histology cites this paper.

Tractography-Driven Synthetic Data Generation for Fiber Bundle Segmentation in Tracer Histology Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-07-04T13:09:51.351932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-26T05:25:43.995059Z digest=sha256:6f80c8e5e657b1406921426b3b2f67f84da99749114e33347afd7cbb4e915900

Observation 6c8ef392-11b3-4e7a-8a8f-f86a550eba42 · inbound

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

Towards Voxel Spacing Consistency for Medical Image Segmentation Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 24

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T10:05:41.112842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-07-01T05:52:47.018861Z digest=sha256:ba68c780308398353413eee8ea7c1b7c7382e2200273b9882058e357eb9749c2

Observation f70d7243-60fe-446a-8cc6-06163f1f305f · inbound

Higher-Order Cell Tracking Transformer cites this paper.

Higher-Order Cell Tracking Transformer Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 61

Resolution
unresolved
no resolver link, observed 2026-07-14T03:25:28.859078Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T03:25:28.859078Z digest=sha256:fa4467c2d0f479c3ebdc6dc6fe5279e6fb54a1d4cdbba990776b2d460836a02c

Observation 7c32a00c-fd24-46bb-8cb1-f756a4b92a4e · inbound

SAMRI-3D: Adapting SAM2 for 3D MRI Segmentation with Global Volume Tokens cites this paper.

SAMRI-3D: Adapting SAM2 for 3D MRI Segmentation with Global Volume Tokens Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-01T16:27:27.835749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T16:27:27.835749Z digest=sha256:c6758700c680f2cb90d3b5960110b5c4b6d2fb36673186e419c566c658ac8a0f

Observation 9d6bdf99-d138-429f-9659-f56ee41c8642 · inbound

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

Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2 Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-01T11:43:13.069270Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T11:43:13.069270Z digest=sha256:610475c5c632dc7ec5aa33b098364551ea9f271ead1c57e987f0fdd486ad0dff

Observation e236232f-e10e-424e-acc9-0cbefc97814c · 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 Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-01T11:31:10.166155Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T11:31:10.166155Z digest=sha256:442a68f82bcfc64dd5445a6fcafe2ea36a7f44822489238f31be21a1d8119b34

Observation d3b75753-d804-450d-8b7a-0a459c053399 · 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 Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 30

Resolution
unresolved
no resolver link, observed 2026-07-30T15:42:49.143667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T15:42:49.143667Z digest=sha256:40a9b0aeba116f1bba25de2f7022ac9bd5371ec6ef7da74a2db358086999fff2

Observation 1a03e6e4-8662-487d-9b14-15e3d96639a6 · inbound

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

Do Medical Foundation Models Generalize on the African Brain? Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-03T00:28:10.669549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T00:28:10.669549Z digest=sha256:87e420920b716b2c11d8e4642f37d22490bee3799686c44daf92312865bc22a8

Observation fac99308-8b69-44c3-94ad-88515e090351 · 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 Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-03T15:00:02.337984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:00:02.337984Z digest=sha256:1ff6fc26177b72e5492d7b935c4f82972d2a7456b95aff36901a5eee0c3d613e