Federated Client-tailored Adapter for Medical Image Segmentation | Paper Citation Record

Observation eb9c7aa4-1795-4070-b000-e7abb65f8fec · outbound

This paper cites Anatomy-aided deep learning for medical image segmentation: a review,.

Federated Client-tailored Adapter for Medical Image Segmentation Anatomy-aided deep learning for medical image segmentation: a review,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:04.062168Z

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Observation 444cec9a-e6fb-422d-9823-34d8853242ef · outbound

This paper cites Segmentation of the multimodal brain tumor image used the multi-pathway architecture method based on 3d fcn,.

Federated Client-tailored Adapter for Medical Image Segmentation Segmentation of the multimodal brain tumor image used the multi-pathway architecture method based on 3d fcn,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:04.041815Z

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Observation 91ecbf79-af0c-4438-80b5-14e035d85f23 · outbound

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

Federated Client-tailored Adapter for Medical Image Segmentation U-net: Convolutional networks for biomedical image segmentation,

Reference 3

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Observation a8f25c80-478f-491a-927a-749a8e555b34 · outbound

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

Federated Client-tailored Adapter for Medical Image Segmentation nnu-net: a self-configuring method for deep learning-based biomedical image segmentation,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:04.009699Z

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Observation 7d1854e9-3f75-4985-9855-0ead91476ed2 · outbound

This paper cites A nested u-net architecture for medical image segmentation,.

Federated Client-tailored Adapter for Medical Image Segmentation A nested u-net architecture for medical image segmentation,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.993320Z

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Observation 88e09ec6-a117-4ff7-859b-545288b2871b · outbound

This paper cites Cotr: Efficiently bridging cnn and transformer for 3d medical image segmentation,.

Federated Client-tailored Adapter for Medical Image Segmentation Cotr: Efficiently bridging cnn and transformer for 3d medical image segmentation,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.979567Z

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Observation 4f0e2020-b023-4ce2-9265-458f05973c7d · outbound

This paper cites Resvit: residual vision transformers for multimodal medical image synthesis,.

Federated Client-tailored Adapter for Medical Image Segmentation Resvit: residual vision transformers for multimodal medical image synthesis,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-16T10:31:02.718293Z

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Observation 612080a0-943c-4955-a1c7-52aeb05c1a7f · outbound

This paper cites Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation.

Federated Client-tailored Adapter for Medical Image Segmentation Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-16T10:31:02.726201Z

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Observation 4fb61e29-ad09-41e9-a957-ec57243081ba · outbound

This paper cites Universeg: Universal medical image segmentation,.

Federated Client-tailored Adapter for Medical Image Segmentation Universeg: Universal medical image segmentation,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.951329Z

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Observation 6b64a160-cae7-4049-94e7-64f8df902f3d · outbound

This paper cites SAM-Med2D.

Federated Client-tailored Adapter for Medical Image Segmentation SAM-Med2D

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-16T10:31:02.736438Z

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Observation f7244e45-97cd-41a7-a24f-e4b14a1ff8c3 · outbound

This paper cites Privacy-preserving object detection for medical images with faster r-cnn,.

Federated Client-tailored Adapter for Medical Image Segmentation Privacy-preserving object detection for medical images with faster r-cnn,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.938710Z

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Observation 8478d66d-0094-4c06-a073-f40298cc7e3b · outbound

This paper cites Privacy-enhanced federated learning against poisoning adversaries,.

Federated Client-tailored Adapter for Medical Image Segmentation Privacy-enhanced federated learning against poisoning adversaries,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.923254Z

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Observation 288b7a9b-ba07-42bc-92f8-3210f1386954 · outbound

This paper cites Federated semi- supervised learning for medical image segmentation via pseudo-label denoising,.

Federated Client-tailored Adapter for Medical Image Segmentation Federated semi- supervised learning for medical image segmentation via pseudo-label denoising,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.908218Z

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Observation 306f42bf-e1d0-46a6-ad81-05214bd79999 · outbound

This paper cites Cross-modal federated human activity recognition,.

Federated Client-tailored Adapter for Medical Image Segmentation Cross-modal federated human activity recognition,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.890977Z

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Observation a9d13e5c-57f4-4235-9cc6-1bb6a92eff36 · outbound

This paper cites Communication-efficient learning of deep networks from decentralized data,.

Federated Client-tailored Adapter for Medical Image Segmentation Communication-efficient learning of deep networks from decentralized data,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-16T10:31:02.761235Z

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Observation 6e37e4b4-8cb9-4c0c-b69b-37661c59a33d · outbound

This paper cites Memory-aware curriculum federated learning for breast cancer classification,.

Federated Client-tailored Adapter for Medical Image Segmentation Memory-aware curriculum federated learning for breast cancer classification,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.866873Z

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Observation 8b22207c-4498-469c-b1f9-aa530f337ab2 · outbound

This paper cites Iop-fl: inside-outside person- alization for federated medical image segmentation,.

Federated Client-tailored Adapter for Medical Image Segmentation Iop-fl: inside-outside person- alization for federated medical image segmentation,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.850370Z

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Observation d46064bc-c44f-4c36-b41c-ce69c6f07596 · outbound

This paper cites Fedseg: Class-heterogeneous federated learning for semantic segmentation,.

Federated Client-tailored Adapter for Medical Image Segmentation Fedseg: Class-heterogeneous federated learning for semantic segmentation,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.833461Z

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Observation 97ca3d60-6c37-4fa1-a385-f57f71c1201c · outbound

This paper cites Cd2-pfed: Cyclic distillation-guided channel decoupling for model personalization in federated learning,.

Federated Client-tailored Adapter for Medical Image Segmentation Cd2-pfed: Cyclic distillation-guided channel decoupling for model personalization in federated learning,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.818327Z

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Observation 5cace1c5-d87d-4581-8b9e-f8b16f9e9eec · outbound

This paper cites pflfe: Cross-silo personalized federated learning via feature enhancement on medical image segmentation,.

Federated Client-tailored Adapter for Medical Image Segmentation pflfe: Cross-silo personalized federated learning via feature enhancement on medical image segmentation,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.672388Z

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Observation a587885d-af6f-4f66-b9bd-29ce0140cd4f · outbound

This paper cites Towards optimal customized architecture for heterogeneous federated learning with contrastive cloud-edge model decoupling,.

Federated Client-tailored Adapter for Medical Image Segmentation Towards optimal customized architecture for heterogeneous federated learning with contrastive cloud-edge model decoupling,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.648457Z

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Observation 8247badb-cb9d-482d-b301-3e945fd94c0c · outbound

This paper cites TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation.

Federated Client-tailored Adapter for Medical Image Segmentation TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-16T10:31:02.800599Z

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Observation b1d49574-d3f0-419f-9967-c6da25bbe0e2 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Federated Client-tailored Adapter for Medical Image Segmentation An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-16T10:31:02.807393Z

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Observation 2d46927d-c3bc-4593-b7b9-e5b6f6d0d7a8 · outbound

This paper cites VM-UNet: Vision Mamba UNet for Medical Image Segmentation.

Federated Client-tailored Adapter for Medical Image Segmentation VM-UNet: Vision Mamba UNet for Medical Image Segmentation

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-16T10:31:02.813779Z

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Observation daeab34d-5e14-4fae-a203-19f426bf9b60 · outbound

This paper cites Compositional prompting video-language models to understand procedure in instructional videos,.

Federated Client-tailored Adapter for Medical Image Segmentation Compositional prompting video-language models to understand procedure in instructional videos,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.632122Z

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Observation 5a25b177-b935-438b-a768-92ef25014b1d · outbound

This paper cites Contrastive learning via local activity,.

Federated Client-tailored Adapter for Medical Image Segmentation Contrastive learning via local activity,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.619868Z

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Observation 37acd855-507e-41e6-adeb-e00d01658d30 · outbound

This paper cites Joint learning in the spatio-temporal and frequency domains for skeleton-based action recognition,.

Federated Client-tailored Adapter for Medical Image Segmentation Joint learning in the spatio-temporal and frequency domains for skeleton-based action recognition,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.607286Z

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Observation e8268319-8e6e-47f2-a817-03e0eeb90f8d · outbound

This paper cites Information-density masking strategy for masked image modeling,.

Federated Client-tailored Adapter for Medical Image Segmentation Information-density masking strategy for masked image modeling,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.593640Z

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Observation 2e2f6d22-c2de-4c86-b738-27f93e9b2991 · outbound

This paper cites Segment anything in medical images,.

Federated Client-tailored Adapter for Medical Image Segmentation Segment anything in medical images,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-16T10:31:02.841837Z

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Observation 190e0430-8f2c-498a-934f-d8e1633a2af3 · outbound

This paper cites nnSAM: Plug-and-play Segment Anything Model Improves nnUNet Performance.

Federated Client-tailored Adapter for Medical Image Segmentation nnSAM: Plug-and-play Segment Anything Model Improves nnUNet Performance

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-08-16T10:31:03.100912Z

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Observation babc32ab-22d4-44b3-9233-2cd7033e5064 · outbound

This paper cites Nwpu-moc: A benchmark for fine-grained multi-category object counting in aerial images,.

Federated Client-tailored Adapter for Medical Image Segmentation Nwpu-moc: A benchmark for fine-grained multi-category object counting in aerial images,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.569201Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 32b1e2cd-d4f7-4d8c-84cf-a03c762aed7f · outbound

This paper cites Contrastive tokens and label activation for remote sensing weakly supervised semantic segmentation,.

Federated Client-tailored Adapter for Medical Image Segmentation Contrastive tokens and label activation for remote sensing weakly supervised semantic segmentation,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.554304Z

Source-reported events for the cited work

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Observation 323db923-2c0b-4762-ad4d-3e44210f2997 · outbound

This paper cites Feddc: Federated learning with non-iid data via local drift decoupling and correction,.

Federated Client-tailored Adapter for Medical Image Segmentation Feddc: Federated learning with non-iid data via local drift decoupling and correction,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.540443Z

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Observation 6ca62dcd-ae84-4ee4-bef1-0fcc09689038 · outbound

This paper cites Federated optimization in heterogeneous networks,.

Federated Client-tailored Adapter for Medical Image Segmentation Federated optimization in heterogeneous networks,

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-16T10:31:02.867393Z

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Observation 86de4ef0-6dc0-43ed-85f0-0b976dabf7ce · outbound

This paper cites Closing the generalization gap of cross- silo federated medical image segmentation,.

Federated Client-tailored Adapter for Medical Image Segmentation Closing the generalization gap of cross- silo federated medical image segmentation,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.518577Z

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Observation d92fc16c-e35b-4d87-a106-f10ab325c749 · outbound

This paper cites Tackling data heterogeneity in federated learning with class prototypes,.

Federated Client-tailored Adapter for Medical Image Segmentation Tackling data heterogeneity in federated learning with class prototypes,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.505843Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ddfc7938-f8e9-4a39-8639-89ff9e001aaa · outbound

This paper cites Fed-cbs: A heterogeneity-aware client sampling mechanism for federated learning via class-imbalance reduction,.

Federated Client-tailored Adapter for Medical Image Segmentation Fed-cbs: A heterogeneity-aware client sampling mechanism for federated learning via class-imbalance reduction,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.493744Z

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Observation ff82ad96-e83b-4d01-90d4-efd0320989ca · outbound

This paper cites Scaffold: Stochastic controlled averaging for federated learn- ing,.

Federated Client-tailored Adapter for Medical Image Segmentation Scaffold: Stochastic controlled averaging for federated learn- ing,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.479796Z

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.

Observation c2a31aa4-8159-4701-981e-0c3eb003bbb0 · outbound

This paper cites Fednp: Towards non-iid federated learning via federated neural propagation,.

Federated Client-tailored Adapter for Medical Image Segmentation Fednp: Towards non-iid federated learning via federated neural propagation,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.465570Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0535abb3-372a-452b-b528-625fedb50155 · outbound

This paper cites Fedst: Federated style transfer learning for non-iid image segmentation,.

Federated Client-tailored Adapter for Medical Image Segmentation Fedst: Federated style transfer learning for non-iid image segmentation,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.450486Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation bbc91232-fb4e-4d62-b542-7df6218539ea · outbound

This paper cites Feda3i: Annotation quality- aware aggregation for federated medical image segmentation against heterogeneous annotation noise,.

Federated Client-tailored Adapter for Medical Image Segmentation Feda3i: Annotation quality- aware aggregation for federated medical image segmentation against heterogeneous annotation noise,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.435449Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3ec31a8c-a3a9-4f9b-9dcd-2a15fef17d8d · outbound

This paper cites Fsar: Federated skeleton-based action recognition with adaptive topology structure and knowledge distillation,.

Federated Client-tailored Adapter for Medical Image Segmentation Fsar: Federated skeleton-based action recognition with adaptive topology structure and knowledge distillation,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.421341Z

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Observation 49c95b33-aba8-4aaf-a7ac-339b84a59e6d · outbound

This paper cites Segment anything,.

Federated Client-tailored Adapter for Medical Image Segmentation Segment anything,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.407774Z

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Observation 9fb68245-40eb-4386-b5d0-91a442bfb2fc · outbound

This paper cites Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning.

Federated Client-tailored Adapter for Medical Image Segmentation Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-16T10:31:02.917007Z

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Observation c7d46a3f-7bc9-4548-b6c5-328822fef0e8 · outbound

This paper cites Segment anything model for medical image segmentation: Current applications and future directions,.

Federated Client-tailored Adapter for Medical Image Segmentation Segment anything model for medical image segmentation: Current applications and future directions,

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-16T10:31:02.922044Z

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Observation 8dccf59c-5c80-46af-afe9-a6edb9dc85b6 · outbound

This paper cites Harmofl: Harmonizing local and global drifts in federated learning on heterogeneous medical images,.

Federated Client-tailored Adapter for Medical Image Segmentation Harmofl: Harmonizing local and global drifts in federated learning on heterogeneous medical images,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.386188Z

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.

Observation 43e51d50-f9c8-47ee-b5c9-971251e3b62f · outbound

This paper cites Personalized and privacy-preserving federated heterogeneous medical image analysis with pppml-hmi,.

Federated Client-tailored Adapter for Medical Image Segmentation Personalized and privacy-preserving federated heterogeneous medical image analysis with pppml-hmi,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.370968Z

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.

Observation bc5513e1-36d0-483c-b01c-9653a0cce543 · outbound

This paper cites Federated cross learning for medical image segmentation,.

Federated Client-tailored Adapter for Medical Image Segmentation Federated cross learning for medical image segmentation,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.357646Z

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.

Observation 8293c894-c317-493a-a773-8e351f7134d6 · outbound

This paper cites Map: model aggregation and personalization in federated learning with incomplete classes,.

Federated Client-tailored Adapter for Medical Image Segmentation Map: model aggregation and personalization in federated learning with incomplete classes,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.344021Z

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.

Observation 9272dda1-078a-45b7-a07b-c0fe33c9a20c · outbound

This paper cites Dynamic strip convolution and adaptive morphology perception plugin for medical anatomy segmentation,.

Federated Client-tailored Adapter for Medical Image Segmentation Dynamic strip convolution and adaptive morphology perception plugin for medical anatomy segmentation,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.329961Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation adabd3a9-c74c-4be8-8ee8-1d5570256dfd · outbound

This paper cites Fedproc: Prototypical contrastive federated learning on non-iid data,.

Federated Client-tailored Adapter for Medical Image Segmentation Fedproc: Prototypical contrastive federated learning on non-iid data,

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-16T10:31:02.956785Z

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Observation e54544a9-7a50-4df6-b191-5ab425e4bfd9 · outbound

This paper cites Feddp: Dual personaliza- tion in federated medical image segmentation,.

Federated Client-tailored Adapter for Medical Image Segmentation Feddp: Dual personaliza- tion in federated medical image segmentation,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.304848Z

Source-reported events for the cited work

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Observation be841e23-937e-4002-aa35-1aad541c2f14 · outbound

This paper cites covid-19-xray-dataset, https://github.com/v7labs/covid- 19-xray-dataset,.

Federated Client-tailored Adapter for Medical Image Segmentation covid-19-xray-dataset, https://github.com/v7labs/covid- 19-xray-dataset,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.289408Z

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.

Observation 15e53dcf-8c1e-45e5-b36c-8bda52dfb0cb · outbound

This paper cites COVID-19 Image Data Collection: Prospective Predictions Are the Future.

Federated Client-tailored Adapter for Medical Image Segmentation COVID-19 Image Data Collection: Prospective Predictions Are the Future

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-16T10:31:02.975309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5bc40eb1-f135-4272-962d-2b6ac1a1aef2 · outbound

This paper cites Osegnet: Operational segmentation network for covid-19 detection using chest x-ray images,.

Federated Client-tailored Adapter for Medical Image Segmentation Osegnet: Operational segmentation network for covid-19 detection using chest x-ray images,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.261677Z

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.

Observation 83a5a46b-9b8c-4109-924c-bf6fcc65ee66 · outbound

This paper cites covid-19-chest-xray-segmentations-dataset, https://github.com/generalblockchain/covid-19-chest-xray- segmentations-dataset,.

Federated Client-tailored Adapter for Medical Image Segmentation covid-19-chest-xray-segmentations-dataset, https://github.com/generalblockchain/covid-19-chest-xray- segmentations-dataset,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.248554Z

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.

Observation f0b9c268-60c7-4249-bdd1-d5244f32ad3d · outbound

This paper cites Amd-sd: An optical coherence tomography image dataset for wet amd lesions segmentation,.

Federated Client-tailored Adapter for Medical Image Segmentation Amd-sd: An optical coherence tomography image dataset for wet amd lesions segmentation,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.234048Z

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.

Observation 863e30de-c0ee-46a6-b389-240b29a19b29 · outbound

This paper cites Unleashing the potential of sam for medical adaptation via hierarchical decoding,.

Federated Client-tailored Adapter for Medical Image Segmentation Unleashing the potential of sam for medical adaptation via hierarchical decoding,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:31:03.219501Z

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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