Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation | Paper Citation Record

Observation edd8e33e-21ed-4d78-b515-d2f7535bae18 · outbound

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

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation U-net: Convolutional networks for biomedical image segmentation,

Reference 1

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This paper cites H-denseunet: hybrid densely connected unet for liver and tumor segmentation from ct volumes,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation H-denseunet: hybrid densely connected unet for liver and tumor segmentation from ct volumes,

Reference 2

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Observation e3c9ce8f-235e-4898-aa12-55e42bff9135 · outbound

This paper cites Segmentation of arm ultrasound images in breast cancer- related lymphedema: A database and deep learning algorithm,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Segmentation of arm ultrasound images in breast cancer- related lymphedema: A database and deep learning algorithm,

Reference 3

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Observation 04474b9b-59c1-404b-a3ea-7afd9b777399 · outbound

This paper cites Shape-aware meta-learning for generalizing prostate mri segmentation to unseen domains,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Shape-aware meta-learning for generalizing prostate mri segmentation to unseen domains,

Reference 4

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Observation aef5c9b7-1560-42a8-a02d-863e51773af8 · outbound

This paper cites Cddsa: Contrastive domain disentanglement and style augmentation for generalizable medical image segmentation,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Cddsa: Contrastive domain disentanglement and style augmentation for generalizable medical image segmentation,

Reference 5

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Observation 7c1ec331-ea56-4275-99b3-c5b90bf9ca1d · outbound

This paper cites Swin-unet: Unet-like pure transformer for medical image segmenta- tion,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Swin-unet: Unet-like pure transformer for medical image segmenta- tion,

Reference 6

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Observation 0cbfbe19-6e94-4f0d-aa7a-e1f8a22e8118 · outbound

This paper cites Medical sam adapter: Adapting segment anything model for medical image segmentation,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Medical sam adapter: Adapting segment anything model for medical image segmentation,

Reference 7

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Observation 3f59f1d9-ade5-4732-9d9d-8f5a597f0af0 · outbound

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

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation VM-UNet: Vision Mamba UNet for Medical Image Segmentation

Reference 8

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Observation d1da633d-23ca-4705-8e50-f6d943d086a2 · outbound

This paper cites Semi-supervised meta-learning with disentanglement for domain-generalised medical image segmentation,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Semi-supervised meta-learning with disentanglement for domain-generalised medical image segmentation,

Reference 9

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Observation 545937fd-ff92-425a-aca7-5fd652be944e · outbound

This paper cites Structure- preserving color normalization and sparse stain separation for histolog- ical images,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Structure- preserving color normalization and sparse stain separation for histolog- ical images,

Reference 10

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Observation 1c5d279d-8a83-45a7-9985-b4a1ab2a0373 · outbound

This paper cites Domain gen- eralization in restoration of cataract fundus images via high-frequency components,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Domain gen- eralization in restoration of cataract fundus images via high-frequency components,

Reference 11

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Observation df93b262-bbc7-4404-ae2f-04c0144ae741 · outbound

This paper cites Generalizable cross- modality medical image segmentation via style augmentation and dual normalization,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Generalizable cross- modality medical image segmentation via style augmentation and dual normalization,

Reference 12

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Observation 4c81d5e4-7414-49ca-9efb-fd46ed6e59fb · outbound

This paper cites Domain generalization for mammography detection via multi-style and multi-view contrastive learning,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Domain generalization for mammography detection via multi-style and multi-view contrastive learning,

Reference 13

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Observation 11b157ec-190c-4827-be0f-37a9ff870e71 · outbound

This paper cites Aadg: Automatic augmentation for domain generalization on retinal image segmentation,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Aadg: Automatic augmentation for domain generalization on retinal image segmentation,

Reference 14

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Observation 00447a6a-d9ed-4783-a587-18bd588b5574 · outbound

This paper cites Improving vision transformers by revisiting high-frequency components,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Improving vision transformers by revisiting high-frequency components,

Reference 15

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Observation 02f598fb-fe2b-4442-b05a-c408e328f73c · outbound

This paper cites Dimix: Disentangle-and-mix based do- main generalizable medical image segmentation,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Dimix: Disentangle-and-mix based do- main generalizable medical image segmentation,

Reference 16

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Observation acb31aad-9e3c-4447-a7e9-8d302c286480 · outbound

This paper cites Transformers in medical imaging: A survey,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Transformers in medical imaging: A survey,

Reference 17

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Observation 47f14524-a1f7-4fbc-932c-2b7acd37572d · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 18

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Observation c56c02f2-e717-4a5e-98d7-b96fc102b37d · outbound

This paper cites Log-vmamba: Local- global vision mamba for medical image segmentation,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Log-vmamba: Local- global vision mamba for medical image segmentation,

Reference 19

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Observation fd5aa107-d7aa-407b-bc76-532c63d436f7 · outbound

This paper cites Mambavision: A hybrid mamba- transformer vision backbone,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Mambavision: A hybrid mamba- transformer vision backbone,

Reference 20

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Observation 5a04f8d0-f4ff-4e43-9d66-089748cbaa11 · outbound

This paper cites VSSD: Vision Mamba with Non-Causal State Space Duality.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation VSSD: Vision Mamba with Non-Causal State Space Duality

Reference 21

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Observation fa95669e-ffb3-4c15-9d95-a69fbea9c6ea · outbound

This paper cites MedMamba: Vision Mamba for Medical Image Classification.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation MedMamba: Vision Mamba for Medical Image Classification

Reference 22

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Observation d49c02cd-7e24-4b4e-a262-d8c26d5a4019 · outbound

This paper cites Vision mamba for classification of breast ultrasound images,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Vision mamba for classification of breast ultrasound images,

Reference 23

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Observation cfbd343e-1ae5-4d7a-add7-1bbb89f9f534 · outbound

This paper cites Mamba-UNet: UNet-Like Pure Visual Mamba for Medical Image Segmentation.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Mamba-UNet: UNet-Like Pure Visual Mamba for Medical Image Segmentation

Reference 24

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Observation 407ed772-ffcd-41fe-836f-b01459064cbd · outbound

This paper cites Polyp-mamba: Polyp segmentation with visual mamba,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Polyp-mamba: Polyp segmentation with visual mamba,

Reference 25

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Observation 07ee793c-11a4-4f39-8501-3e9095aeb3bf · outbound

This paper cites Segmamba: Long-range sequential modeling mamba for 3d medical image segmentation,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Segmamba: Long-range sequential modeling mamba for 3d medical image segmentation,

Reference 26

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Observation 6d5f4d3d-a854-487b-82fb-85ebec8d5fe0 · outbound

This paper cites HC-Mamba: Vision MAMBA with Hybrid Convolutional Techniques for Medical Image Segmentation.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation HC-Mamba: Vision MAMBA with Hybrid Convolutional Techniques for Medical Image Segmentation

Reference 27

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This paper cites UltraLight VM-UNet: Parallel Vision Mamba Significantly Reduces Parameters for Skin Lesion Segmentation.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation UltraLight VM-UNet: Parallel Vision Mamba Significantly Reduces Parameters for Skin Lesion Segmentation

Reference 28

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Observation fd7fa598-522b-408a-8269-3ffebd568ded · outbound

This paper cites Segment anything,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Segment anything,

Reference 29

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This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation LoRA: Low-Rank Adaptation of Large Language Models

Reference 30

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This paper cites Multi- centre, multi-vendor and multi-disease cardiac segmentation: the m&ms challenge,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Multi- centre, multi-vendor and multi-disease cardiac segmentation: the m&ms challenge,

Reference 31

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Observation c7115b0e-6070-4c15-908f-c12af868a975 · outbound

This paper cites Dofe: Domain-oriented feature embedding for generalizable fundus image segmentation on unseen datasets,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Dofe: Domain-oriented feature embedding for generalizable fundus image segmentation on unseen datasets,

Reference 32

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Observation 9f2343ce-698b-45d2-8eaa-c92b044e8e5d · outbound

This paper cites Minimax estimation of maximum mean discrepancy with radial kernels,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Minimax estimation of maximum mean discrepancy with radial kernels,

Reference 33

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Observation 17fedb07-3665-473f-bc42-3ca83e26f5fb · outbound

This paper cites VMamba: Visual state space model,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation VMamba: Visual state space model,

Reference 34

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Observation 5c403a92-fc68-4d35-956a-6e21ea366418 · outbound

This paper cites U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation

Reference 35

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Observation e338669c-2704-4395-90a6-12939999d2dc · outbound

This paper cites Start: A generalized state space model with saliency-driven token-aware transformation,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Start: A generalized state space model with saliency-driven token-aware transformation,

Reference 36

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Observation 3aed54db-94a3-4de7-b118-1d915b00897d · outbound

This paper cites Domain and content adaptive convolution based multi-source domain generalization for medical image segmentation,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Domain and content adaptive convolution based multi-source domain generalization for medical image segmentation,

Reference 37

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Observation 74c1fd08-627d-48c6-b1fe-aa48bc69d140 · outbound

This paper cites Feddg: Federated domain generalization on medical image segmentation via episodic learning in continuous frequency space,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Feddg: Federated domain generalization on medical image segmentation via episodic learning in continuous frequency space,

Reference 38

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Observation 7b1d0b9d-6c65-4379-b1ca-22bdaec1e136 · outbound

This paper cites Do- main generalization via model-agnostic learning of semantic features,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Do- main generalization via model-agnostic learning of semantic features,

Reference 39

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Observation 3a835301-08e5-4570-9333-cb0b61ed831b · outbound

This paper cites Random style transfer based domain generalization net- works integrating shape and spatial information,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Random style transfer based domain generalization net- works integrating shape and spatial information,

Reference 40

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Observation e15e5bff-ac89-4343-ac15-233e03426484 · outbound

This paper cites Tesla: Test-time self-learning with automatic adversarial augmentation,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Tesla: Test-time self-learning with automatic adversarial augmentation,

Reference 41

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Observation d9c585d6-6d39-4de7-950b-7d2b96777a5a · outbound

This paper cites Vm-unet-v2: Rethinking vision mamba unet for medical image segmentation,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Vm-unet-v2: Rethinking vision mamba unet for medical image segmentation,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:42:23.752243Z

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Observation 0ee04a4a-f259-4627-a53b-8549cc62ed02 · outbound

This paper cites LKM-UNet: Large Kernel Vision Mamba UNet for Medical Image Segmentation.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation LKM-UNet: Large Kernel Vision Mamba UNet for Medical Image Segmentation

Reference 43

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Observation e50d0c4a-36c5-46c4-96ea-078c94eaa180 · outbound

This paper cites ViM-UNet: Vision Mamba for Biomedical Segmentation.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation ViM-UNet: Vision Mamba for Biomedical Segmentation

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-16T10:42:23.003578Z

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Observation 17fed982-3fa1-4fd2-97b1-6b5c1ba19840 · outbound

This paper cites CAMS: Convolution and Attention-Free Mamba-based Cardiac Image Segmentation.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation CAMS: Convolution and Attention-Free Mamba-based Cardiac Image Segmentation

Reference 45

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Observation 7a23dff3-df50-4bbb-9723-c934d165c817 · outbound

This paper cites Efficiently Modeling Long Sequences with Structured State Spaces.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Efficiently Modeling Long Sequences with Structured State Spaces

Reference 46

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Observation 73a0f753-b974-4706-ae29-6a4eafd4f330 · outbound

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

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation nnu-net: a self-configuring method for deep learning-based biomedical image segmentation,

Reference 47

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Observation 1d637a5c-9629-4c84-a7fd-b7d49f6de232 · outbound

This paper cites Medsrgan: medical images super-resolution using generative adversarial networks,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Medsrgan: medical images super-resolution using generative adversarial networks,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:42:23.730150Z

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Observation a51882fc-89c5-47c3-810d-8c165da4322d · outbound

This paper cites On the proper use of structural similarity for the robust evaluation of medical image synthesis models,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation On the proper use of structural similarity for the robust evaluation of medical image synthesis models,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:42:23.715546Z

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Observation a8ae90bb-67be-4e2b-9684-327fa38f8319 · outbound

This paper cites Toward fast, flexible, and robust low-light image enhancement,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Toward fast, flexible, and robust low-light image enhancement,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:42:23.700080Z

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Observation bf9fd96a-298a-426c-a5c8-590871edb5a2 · outbound

This paper cites Vision mamba: Efficient visual representation learning with bidirectional state space model,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Vision mamba: Efficient visual representation learning with bidirectional state space model,

Reference 51

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Observation 6df4a982-062d-4963-b7f0-57b7fe54404d · outbound

This paper cites Domain generalization with mixstyle,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Domain generalization with mixstyle,

Reference 52

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Observation 229e7356-a3b2-4040-a5c5-3a68f806e15e · outbound

This paper cites Aloft: A lightweight mlp- like architecture with dynamic low-frequency transform for domain generalization,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Aloft: A lightweight mlp- like architecture with dynamic low-frequency transform for domain generalization,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:42:23.668949Z

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Observation f3405239-024e-4990-8995-e7214ba70d5d · outbound

This paper cites A comprehensive retinal image dataset for the assessment of glaucoma from the optic nerve head analysis,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation A comprehensive retinal image dataset for the assessment of glaucoma from the optic nerve head analysis,

Reference 54

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Observation 7cd10198-4e26-48da-9362-5c64b500ded9 · outbound

This paper cites Rim-one: An open retinal image database for optic nerve evaluation,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Rim-one: An open retinal image database for optic nerve evaluation,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:42:23.645712Z

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Observation 71baa9e0-09b8-4659-9799-a66da7b7e080 · outbound

This paper cites Refuge challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Refuge challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:42:23.632549Z

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Observation 8038ef6e-ef43-4c21-abf7-35bf2f332dfe · outbound

This paper cites Nci- isbi 2013 challenge: automated segmentation of prostate structures,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Nci- isbi 2013 challenge: automated segmentation of prostate structures,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:42:23.619316Z

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Observation f4e84ff1-f6bf-40a4-be18-809467c42140 · outbound

This paper cites Computer-aided detection and diagnosis for prostate cancer based on mono and multi-parametric mri: a review,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Computer-aided detection and diagnosis for prostate cancer based on mono and multi-parametric mri: a review,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:42:23.605731Z

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Observation bbeeb306-a1dd-473c-8fa4-f5ec45bbee00 · outbound

This paper cites Evaluation of prostate segmentation algorithms for mri: the promise12 challenge,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Evaluation of prostate segmentation algorithms for mri: the promise12 challenge,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:42:23.592588Z

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Observation 47271869-0871-4f61-b5ba-6d25c73032c1 · outbound

This paper cites Domain generalization by solving jigsaw puzzles,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Domain generalization by solving jigsaw puzzles,

Reference 60

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Observation 05635d4b-3718-40fd-8b87-de2ed893afe8 · outbound

This paper cites Generalizing deep learning for medical image segmentation to unseen domains via deep stacked transformation,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Generalizing deep learning for medical image segmentation to unseen domains via deep stacked transformation,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:42:23.570501Z

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Observation 1075a122-e3d4-4c19-91a7-52a6673e17db · outbound

This paper cites Learning robust shape regularization for generalizable medical image segmentation,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Learning robust shape regularization for generalizable medical image segmentation,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:42:23.556965Z

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Observation 008857fa-dad0-4fac-b977-b401ed55837d · outbound

This paper cites SAM-Med2D.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation SAM-Med2D

Reference 63

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Observation 63c24344-cbda-4844-a7dd-2da08386ee4f · outbound

This paper cites Imagenet: A large-scale hierarchical image database,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Imagenet: A large-scale hierarchical image database,

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-16T10:42:23.085967Z

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Observation dbd71ab7-00ec-4646-9fea-d130b35fe9cd · outbound

This paper cites Cutmix: Reg- ularization strategy to train strong classifiers with localizable features,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Cutmix: Reg- ularization strategy to train strong classifiers with localizable features,

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-16T10:42:23.089896Z

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Observation c3962fbb-4400-4a57-afe6-d8aea6fa23d1 · outbound

This paper cites Visualizing data using t-sne.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Visualizing data using t-sne

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-16T10:42:23.093770Z

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Observation 2f28e9ba-7a3d-4a41-8002-9c8e050266c3 · outbound

This paper cites De-LightSAM: Modality-Decoupled Lightweight SAM for Generalizable Medical Segmentation.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation De-LightSAM: Modality-Decoupled Lightweight SAM for Generalizable Medical Segmentation

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-16T10:42:23.098262Z

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Observation cecc9b06-ebff-4c29-8c08-9e0fa29d25de · outbound

This paper cites The ham10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation The ham10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions,

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-16T10:42:23.102502Z

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Observation 5d4aaee0-30d5-4907-b5d5-cc844fff85bf · outbound

This paper cites Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC).

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-16T10:42:23.106488Z

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Observation ad878b3f-a99d-4154-8fb5-be3fb20a76bd · outbound

This paper cites Ph 2-a dermoscopic image database for research and benchmarking,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Ph 2-a dermoscopic image database for research and benchmarking,

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:42:23.508515Z

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Observation 5f4ad9f1-6097-487e-b169-be426954793d · outbound

This paper cites Sam 2: Segment anything in images and videos,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Sam 2: Segment anything in images and videos,

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:42:23.494871Z

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Observation 124d5287-c4ff-4f4e-88c3-791adb8e01fa · outbound

This paper cites Sam-adapter: Adapting segment anything in underperformed scenes,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Sam-adapter: Adapting segment anything in underperformed scenes,

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-16T10:42:23.119157Z

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Observation fde4a00d-8c5f-4671-a2a2-6eaeb8847cec · outbound

This paper cites Improving the generalization of segmentation foundation model under distribution shift via weakly supervised adaptation,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Improving the generalization of segmentation foundation model under distribution shift via weakly supervised adaptation,

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:42:23.472989Z

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Observation 7c59c168-c27f-4585-a3cb-506d5e2e20ad · outbound

This paper cites Encoder- decoder with atrous separable convolution for semantic image segmen- tation,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Encoder- decoder with atrous separable convolution for semantic image segmen- tation,

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:42:23.458690Z

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Observation 55bd2387-5430-4c2c-b3c0-4604a3365260 · outbound

This paper cites Transunet: Rethinking the u-net architecture design for medical image segmentation through the lens of transformers,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Transunet: Rethinking the u-net architecture design for medical image segmentation through the lens of transformers,

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:42:23.444981Z

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Observation cfcb2f7c-d83d-4c3a-a723-8905f6a18e9e · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Swin transformer: Hierarchical vision transformer using shifted windows,

Reference 76

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Observation 66d9eb28-3edd-4a04-b40e-4ae18e0a0b29 · outbound

This paper cites Transformers are SSMs: Generalized models and efficient algorithms through structured state space duality,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Transformers are SSMs: Generalized models and efficient algorithms through structured state space duality,

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-16T10:42:23.139557Z

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Observation 2411f205-41e3-44bb-ac0e-35ab91d4f05b · outbound

This paper cites Famba-v: Fast vision mamba with cross-layer token fusion,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Famba-v: Fast vision mamba with cross-layer token fusion,

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:42:23.411186Z

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Observation b1880fa9-2211-4adb-9190-6f43a903b9f2 · outbound

This paper cites Segment anything in medical images,.

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation Segment anything in medical images,

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-16T10:42:23.147352Z

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