Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T19:59:54.826704Z
Paper Citation Record · LEDGER
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation
As of 16 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 0 inbound Pith citation observations for arXiv:2411.10136.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
50 of 50 outbound references displayed
- verified exact2
- verified fuzzy30
- unresolved18
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation cfdb8c6b-2a1d-4b6a-aea4-0b04e3008c0f · outbound
This paper cites Mi-segnet: Mu- tual information-based us segmentation for unseen domain generalization.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Mi-segnet: Mu- tual information-based us segmentation for unseen domain generalization
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:59:55.990045Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 09254893-4c05-4349-a607-79cb6fc507f7 · outbound
This paper cites Biosam: Generating sam prompts from superpixel graph for biological instance segmentation.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Biosam: Generating sam prompts from superpixel graph for biological instance segmentation
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:59:55.960190Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 804c4a49-8878-472f-8132-c55fdcaad8f7 · outbound
This paper cites Ma-sam: Modality-agnostic sam adap- tation for 3d medical image segmentation.Med.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Ma-sam: Modality-agnostic sam adap- tation for 3d medical image segmentation.Med
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:59:55.940950Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 84d3dde1-3630-4161-810c-537dc7aa8b10 · outbound
This paper cites Sam-adapter: Adapting segment any- thing in underperformed scenes.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Sam-adapter: Adapting segment any- thing in underperformed scenes
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:59:55.918787Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation ff5d95d8-d933-46e2-a245-bf5215063299 · outbound
This paper cites Treasure in distribution: a domain randomiza- tion based multi-source domain generalization for 2d medi- cal image segmentation.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Treasure in distribution: a domain randomiza- tion based multi-source domain generalization for 2d medi- cal image segmentation
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T19:59:54.518326Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8128446e-da94-469a-98a4-a3c80397d03e · outbound
This paper cites PAM: A Propagation-Based Model for Segmenting Any 3D Objects across Multi-Modal Medical Images.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation PAM: A Propagation-Based Model for Segmenting Any 3D Objects across Multi-Modal Medical Images
Reference 7
- Resolution
- verified exact
- local_arxiv, observed 2026-08-12T19:59:55.251769Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 4410f24f-c9b9-4bee-b210-13c3c650e8e2 · outbound
This paper cites UN-SAM: Universal Prompt-Free Segmentation for Generalized Nuclei Images.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation UN-SAM: Universal Prompt-Free Segmentation for Generalized Nuclei Images
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T19:59:54.535144Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 84934d93-1a29-424b-8828-31bf7ad3fd04 · outbound
This paper cites Unleashing the potential of sam for medical adaptation via hierarchical de- coding.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Unleashing the potential of sam for medical adaptation via hierarchical de- coding
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:59:55.878315Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 4bdcd232-6f1a-4cfa-b45a-9c4c5e598e0d · outbound
This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T19:59:54.548487Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 447a6c01-544b-4fa5-8351-2f995c48ffd9 · outbound
This paper cites Dyno: Dynamic normalization based test-time adaptation for 2d medical image segmentation.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Dyno: Dynamic normalization based test-time adaptation for 2d medical image segmentation
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:59:55.856548Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 74dcd0bb-d974-42b7-a2b5-d1e466c84614 · outbound
This paper cites Desam: Decoupled segment anything model for gen- eralizable medical image segmentation.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Desam: Decoupled segment anything model for gen- eralizable medical image segmentation
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:59:55.832973Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 3e41d191-be64-4b62-bd71-55392e880e2c · outbound
This paper cites Transfer learning for domain adapta- tion in mri: Application in brain lesion segmentation.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Transfer learning for domain adapta- tion in mri: Application in brain lesion segmentation
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:59:55.813064Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation ade269e7-565e-4214-baac-cbb412812b94 · outbound
This paper cites Apseg: Auto-prompt network for cross-domain few-shot semantic segmentation.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Apseg: Auto-prompt network for cross-domain few-shot semantic segmentation
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:59:55.792225Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 5069e5e1-bd55-4083-9fe4-ee82ddb19269 · outbound
This paper cites LoRA: Low-Rank Adaptation of Large Language Models.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation LoRA: Low-Rank Adaptation of Large Language Models
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T19:59:54.584411Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a4712d59-8ae3-41e6-b228-6269874be637 · outbound
This paper cites Domain and content adaptive convolution based multi- source domain generalization for medical image segmenta- tion.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Domain and content adaptive convolution based multi- source domain generalization for medical image segmenta- tion
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:59:55.770944Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 405b8024-0337-41c8-85db-f0105890210b · outbound
This paper cites nnu-net: a self-configuring method for deep learning-based biomedical image segmen- tation.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation nnu-net: a self-configuring method for deep learning-based biomedical image segmen- tation
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:59:55.751301Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 0979f7ae-eee0-4ac7-933c-76a88ca8c75f · outbound
This paper cites Ultralytics yolov8.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Ultralytics yolov8
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:59:55.722988Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation b619cec5-5976-42af-b55d-d2128f607614 · outbound
This paper cites Adam: A Method for Stochastic Optimization.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Adam: A Method for Stochastic Optimization
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T19:59:54.613655Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 93dd0f80-f515-4b14-be7e-57d923ba3d21 · outbound
This paper cites Segment any- thing.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Segment any- thing
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:59:55.702067Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation e8aaff34-e160-4319-8759-1c276daa6a69 · outbound
This paper cites Frequency-mixed single-source domain generalization for medical image segmentation.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Frequency-mixed single-source domain generalization for medical image segmentation
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:59:55.678083Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 6ad6bdf1-615c-4aa8-87d9-f93260780e7f · outbound
This paper cites Asps: Augmented segment anything model for polyp segmentation.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Asps: Augmented segment anything model for polyp segmentation
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:59:55.659338Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 4c7ecb9c-e432-4480-ae0b-2d3ba4787ed4 · outbound
This paper cites Am- sam: Automated prompting and mask calibration for seg- ment anything model.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Am- sam: Automated prompting and mask calibration for seg- ment anything model
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T19:59:54.641026Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ff4a5846-c44c-4816-bae9-6efd30369701 · outbound
This paper cites A survey on active deep learning: from model driven to data driven.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation A survey on active deep learning: from model driven to data driven
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:59:55.639987Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 5a04c9f6-a44b-4395-ad15-0a679544e10f · outbound
This paper cites Shape-aware meta-learning for generalizing prostate mri segmentation to 9 unseen domains.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Shape-aware meta-learning for generalizing prostate mri segmentation to 9 unseen domains
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:59:55.621883Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 46b4d63c-f0ac-433d-b694-bb11291b077e · outbound
This paper cites Semi-supervised meta-learning with disentangle- ment for domain-generalised medical image segmentation.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Semi-supervised meta-learning with disentangle- ment for domain-generalised medical image segmentation
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:59:55.603693Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation cb9bebfd-68c5-4025-895c-bb73fddb496c · outbound
This paper cites Decoupled Weight Decay Regularization.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Decoupled Weight Decay Regularization
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T19:59:54.669067Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 91f648e0-4d1f-4a3e-ada1-4eb3a0ccb488 · outbound
This paper cites Segment anything in medical images.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Segment anything in medical images
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T19:59:54.675238Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 123f1774-0140-4b33-9b6e-eda0100a3a5d · outbound
This paper cites A Survey on Domain Generalization for Medical Image Analysis.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation A Survey on Domain Generalization for Medical Image Analysis
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T19:59:54.682606Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e7240d5a-fee5-493e-b919-820fd7191b81 · outbound
This paper cites Bias in data-driven artificial intelligence systems—an introductory survey.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Bias in data-driven artificial intelligence systems—an introductory survey
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:59:55.572057Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 10101796-dc58-4fd9-811e-730f85cc614f · outbound
This paper cites Refuge challenge: A unified framework for evaluat- ing automated methods for glaucoma assessment from fun- dus photographs.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Refuge challenge: A unified framework for evaluat- ing automated methods for glaucoma assessment from fun- dus photographs
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:59:55.551665Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 47b13350-6032-422c-9f1c-1b2c1b418c07 · outbound
This paper cites S-SAM: SVD-based Fine-Tuning of Segment Anything Model for Medical Image Segmentation.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation S-SAM: SVD-based Fine-Tuning of Segment Anything Model for Medical Image Segmentation
Reference 32
- Resolution
- verified exact
- local_arxiv, observed 2026-08-12T19:59:54.989256Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation de703da9-4694-4f23-99b3-cc544e3aac4b · outbound
This paper cites Db-sam: Delving into high quality universal medical image segmentation.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Db-sam: Delving into high quality universal medical image segmentation
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:59:55.532132Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation e2c236f7-10b5-4815-b1a2-b4c29c9ee861 · outbound
This paper cites Dataset shift in ma- chine learning.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Dataset shift in ma- chine learning
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:59:55.511496Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation bfcb268b-622d-4416-930b-76971aee403a · outbound
This paper cites U-net: Convolutional networks for biomedical image segmentation.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation U-net: Convolutional networks for biomedical image segmentation
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:59:55.490996Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 208e0164-2693-4464-bfd1-05789ba02998 · outbound
This paper cites Learning from synthetic data: Addressing domain shift for semantic segmentation.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Learning from synthetic data: Addressing domain shift for semantic segmentation
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T19:59:54.729977Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b3e43622-a283-4bd0-8d4b-327600c2bc74 · outbound
This paper cites Drishti-gs: Retinal image dataset for optic nerve head (onh) segmentation.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Drishti-gs: Retinal image dataset for optic nerve head (onh) segmentation
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:59:55.455894Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 29cffb9a-fd03-4d04-9f3c-ceaf50a16f12 · outbound
This paper cites Rethinking data augmentation for single-source domain generalization in medical image segmentation.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Rethinking data augmentation for single-source domain generalization in medical image segmentation
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:59:55.428881Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation ee38c947-f2fa-4b44-8dc4-90dd08c88145 · outbound
This paper cites Rethinking domain generalization for face anti- spoofing: Separability and alignment.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Rethinking domain generalization for face anti- spoofing: Separability and alignment
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T19:59:54.748975Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ea761407-2cd7-42f6-bbaa-b239b5b78c83 · outbound
This paper cites Cross-domain face presentation attack detection via multi- domain disentangled representation learning.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Cross-domain face presentation attack detection via multi- domain disentangled representation learning
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:59:55.387774Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 2d3f1981-a2a8-4e01-bdba-095039c8e0a8 · outbound
This paper cites Leveraging SAM for Single-Source Domain Generalization in Medical Image Segmentation.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Leveraging SAM for Single-Source Domain Generalization in Medical Image Segmentation
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T19:59:54.763117Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d23eb09a-b76a-4d05-ab89-394f3e0c9371 · outbound
This paper cites Prompting segment anything model with domain-adaptive prototype for generalizable medical image segmentation.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Prompting segment anything model with domain-adaptive prototype for generalizable medical image segmentation
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:59:55.368064Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 22bb6e0f-43e6-444b-b1b1-28c9e7bfb17c · outbound
This paper cites MaskSAM: Towards Auto-prompt SAM with Mask Classification for Volumetric Medical Image Segmentation.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation MaskSAM: Towards Auto-prompt SAM with Mask Classification for Volumetric Medical Image Segmentation
Reference 43
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T19:59:54.775976Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3ea13a30-efe0-475f-9737-86e98aaaefe0 · outbound
This paper cites Sesv: Accurate medical image segmentation by predicting and correcting errors.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Sesv: Accurate medical image segmentation by predicting and correcting errors
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:59:55.347547Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 235e84b0-52eb-44d1-868b-849b01415d82 · outbound
This paper cites De-LightSAM: Modality-Decoupled Lightweight SAM for Generalizable Medical Segmentation.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation De-LightSAM: Modality-Decoupled Lightweight SAM for Generalizable Medical Segmentation
Reference 45
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T19:59:54.793428Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ecdf1881-a007-4fa1-b19f-2e78b0041d05 · outbound
This paper cites Customized Segment Anything Model for Medical Image Segmentation.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Customized Segment Anything Model for Medical Image Segmentation
Reference 46
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T19:59:54.799165Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 70543a01-7de2-45b6-8645-1cb177496cbf · outbound
This paper cites Origa-light: An online retinal fundus image database for glaucoma analysis and research.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Origa-light: An online retinal fundus image database for glaucoma analysis and research
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:59:55.323382Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 784e2870-853e-4b0c-be80-392b5fdfed64 · outbound
This paper cites Domain Generalization with Adversarial Intensity Attack for Medical Image Segmentation.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Domain Generalization with Adversarial Intensity Attack for Medical Image Segmentation
Reference 48
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T19:59:54.810851Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 526de0c0-d361-4fd8-8c8b-ccbda426f42d · outbound
This paper cites Do- main adaptive ensemble learning.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Do- main adaptive ensemble learning
Reference 49
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T19:59:54.816121Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d5d72b48-b9f6-474c-9a39-7bbd58e96873 · outbound
This paper cites Domain generalization: A survey.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Domain generalization: A survey
Reference 50
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T19:59:54.821183Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ec78e70b-6548-4814-87a8-eafde22dfe04 · outbound
This paper cites Localized adversarial domain generalization.
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation Localized adversarial domain generalization
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:59:55.271818Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Pith citing papers
No inbound Pith citation observations are available.