Paper Citation Record · LEDGER

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images

As of 18 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2506.18042.

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

pith.paper-citation-record.v1
2506.18042 v1

Coverage vector

measured 38 of 38 reference resolution

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One-hop event checks from named stored sources.

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Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

38 of 38 outbound references displayed

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External citation measurements

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Outbound references

Observation 6eda17fc-f010-45af-bc25-f7956b6e408e · outbound

This paper cites Scribble-supervised medical image segmentation via dual-branch net- work and dynamically mixed pseudo labels supervision,.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images Scribble-supervised medical image segmentation via dual-branch net- work and dynamically mixed pseudo labels supervision,

Reference 1

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Observation 0a19b9b3-1640-470e-88b8-93268d7c6f58 · outbound

This paper cites Image segmentation using deep learning: A survey,.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images Image segmentation using deep learning: A survey,

Reference 2

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Observation 6c5136c0-7741-4933-a0b2-aa642489511d · outbound

This paper cites Learning deep features for discriminative localization,.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images Learning deep features for discriminative localization,

Reference 3

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Observation ff9d5812-745b-4bbb-8c1f-a724f91e2399 · outbound

This paper cites Weakly supervised segmentation with cross- modality equivariant constraints,.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images Weakly supervised segmentation with cross- modality equivariant constraints,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:29:21.379291Z

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Observation 5c29532e-dda1-47a5-b3f2-0f3b73df85ea · outbound

This paper cites Dmsps: Dynamically mixed soft pseudo-label supervision for scribble-supervised medical image segmentation,.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images Dmsps: Dynamically mixed soft pseudo-label supervision for scribble-supervised medical image segmentation,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:29:21.037817Z

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Observation 25e6fc35-fe84-44d2-ad39-d9f65fcc0c12 · outbound

This paper cites Scribble2label: Scribble-supervised cell segmentation via self-generating pseudo-labels with consistency,.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images Scribble2label: Scribble-supervised cell segmentation via self-generating pseudo-labels with consistency,

Reference 6

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Observation 23d1dced-5ef2-4aac-8577-7f167ecddcc3 · outbound

This paper cites Deepcut: Object segmentation from bounding box annotations using convolutional neural networks,.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images Deepcut: Object segmentation from bounding box annotations using convolutional neural networks,

Reference 7

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Observation c3902270-3e27-4184-a8cc-997f50e9aa50 · outbound

This paper cites Pa-seg: learning from point annotations for 3d medical image segmentation using contextual regularization and cross knowledge distillation,.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images Pa-seg: learning from point annotations for 3d medical image segmentation using contextual regularization and cross knowledge distillation,

Reference 8

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Observation ecadbbe6-c6e1-421e-91ef-b3245619341c · outbound

This paper cites Scribformer: Transformer makes cnn work better for scribble-based medical image segmentation,.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images Scribformer: Transformer makes cnn work better for scribble-based medical image segmentation,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:29:19.622911Z

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Observation fb8a7712-904d-4e5b-b5c9-ffb2f3f4dbef · outbound

This paper cites Scribblesup: Scribble- supervised convolutional networks for semantic segmentation,.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images Scribblesup: Scribble- supervised convolutional networks for semantic segmentation,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:29:19.328385Z

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Observation 9cd63f7c-fac1-4a5a-8f81-47e7ecae215c · outbound

This paper cites Semi-supervised learning by entropy minimization,.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images Semi-supervised learning by entropy minimization,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:29:19.066898Z

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Observation cb90af17-309b-4cb7-ad7b-4502baef1c0f · outbound

This paper cites Unsupervised Total Variation Loss for Semi-supervised Deep Learning of Semantic Segmentation.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images Unsupervised Total Variation Loss for Semi-supervised Deep Learning of Semantic Segmentation

Reference 12

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Observation ce8630f1-7e24-4627-8681-7f1dcbe2b6e8 · outbound

This paper cites Weakly supervised segmentation of covid19 infection with scribble annotation on ct images,.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images Weakly supervised segmentation of covid19 infection with scribble annotation on ct images,

Reference 13

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Observation 3a8ef3d8-c1e4-4e93-b7c1-d9d161da1424 · outbound

This paper cites A review: Deep learning for medical im- age segmentation using multi-modality fusion,.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images A review: Deep learning for medical im- age segmentation using multi-modality fusion,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:29:18.395470Z

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Observation b290ebf1-183b-4e8c-9809-7316dc8b01c2 · outbound

This paper cites Comparing different ct, pet and mri multi-modality image combinations for deep learning- based head and neck tumor segmentation,.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images Comparing different ct, pet and mri multi-modality image combinations for deep learning- based head and neck tumor segmentation,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:29:18.124120Z

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Observation 044e88dd-0b7e-4c15-9e29-5ea5fe8228fa · outbound

This paper cites Hyperdense-net: a hyper-densely connected cnn for multi-modal image segmentation,.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images Hyperdense-net: a hyper-densely connected cnn for multi-modal image segmentation,

Reference 16

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Observation 52a33250-e459-49a7-8c3e-b56c06c86333 · outbound

This paper cites Flexible fusion network for multi-modal brain tumor segmentation,.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images Flexible fusion network for multi-modal brain tumor segmentation,

Reference 17

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Observation fe974ae1-69db-42ff-995b-1ea346239387 · outbound

This paper cites Modality-aware mutual learning for multi-modal medical image seg- mentation,.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images Modality-aware mutual learning for multi-modal medical image seg- mentation,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:29:17.059049Z

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Observation 8e576031-d455-4198-a500-1a5f75cf35a2 · outbound

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

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images U-net: Convolutional networks for biomedical image segmentation,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:29:16.689982Z

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Observation d706c6f9-7258-4e62-9eba-06664e74069a · outbound

This paper cites 3d u-net: learning dense volumetric segmentation from sparse annota- tion,.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images 3d u-net: learning dense volumetric segmentation from sparse annota- tion,

Reference 20

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Observation efdccac0-9fb5-43ce-b35d-e06130bf964f · outbound

This paper cites Medical Image Segmentation Review: The success of U-Net.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images Medical Image Segmentation Review: The success of U-Net

Reference 21

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Observation 78f9f88b-a831-4c53-90a6-93ff04def0f3 · outbound

This paper cites Unet++: Re- designing skip connections to exploit multiscale features in image segmentation,.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images Unet++: Re- designing skip connections to exploit multiscale features in image segmentation,

Reference 22

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Observation c9a6ea32-04a9-4fe1-b056-15a124dddf95 · outbound

This paper cites Densely connected convolutional networks,.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images Densely connected convolutional networks,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:29:15.450797Z

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Observation f47d4c60-09ae-49f0-bbac-f94c175cdb3a · outbound

This paper cites V-net: Fully convolutional neural networks for volumetric medical image segmentation,.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images V-net: Fully convolutional neural networks for volumetric medical image segmentation,

Reference 24

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Observation a76445ab-4f4e-4d9d-8db4-0c59b19cc033 · outbound

This paper cites 3d reconstruction-oriented fully automatic multi-modal tumor segmentation by dual attention-guided vnet,.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images 3d reconstruction-oriented fully automatic multi-modal tumor segmentation by dual attention-guided vnet,

Reference 25

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Observation 39d78df5-e6e1-4418-a839-dc7016320e48 · outbound

This paper cites Unetr: Transformers for 3d medical image segmentation,.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images Unetr: Transformers for 3d medical image segmentation,

Reference 26

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Observation 805c597e-52fd-49d8-a995-68a1679b6e64 · outbound

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

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 27

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Observation f8b38198-08b6-44be-956a-92047384f752 · outbound

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

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images Transformers are SSMs: Generalized models and efficient algorithms through structured state space duality,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:29:14.349707Z

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Observation 9c6fe240-9edf-4655-886c-e30e2e348bf0 · outbound

This paper cites Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model

Reference 29

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Observation 75619f41-f6a3-49a7-8e7b-7b0f67f07e7a · outbound

This paper cites Delving deep into rectifiers: Surpassing human-level performance on imagenet classification,.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images Delving deep into rectifiers: Surpassing human-level performance on imagenet classification,

Reference 30

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Observation 92a6ce98-755f-41cc-9e1f-f23915403c82 · outbound

This paper cites Word: A large scale dataset, bench- mark and clinical applicable study for abdominal organ segmentation from ct image,.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images Word: A large scale dataset, bench- mark and clinical applicable study for abdominal organ segmentation from ct image,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:29:13.557642Z

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Observation cd904707-432f-4495-8d33-419bfc5d9cfa · outbound

This paper cites Scribble- based 3d multiple abdominal organ segmentation via triple-branch multi- dilated network with pixel-and class-wise consistency,.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images Scribble- based 3d multiple abdominal organ segmentation via triple-branch multi- dilated network with pixel-and class-wise consistency,

Reference 32

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Observation b317f296-f095-4f16-9919-a3d1f78fc73d · outbound

This paper cites User-guided 3d active contour segmentation of anatomical structures: significantly improved efficiency and reliability,.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images User-guided 3d active contour segmentation of anatomical structures: significantly improved efficiency and reliability,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:29:13.008585Z

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Observation 437c411f-07c2-418b-a124-9900fb99e12d · outbound

This paper cites Learning to segment from scribbles using multi-scale adversarial attention gates,.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images Learning to segment from scribbles using multi-scale adversarial attention gates,

Reference 34

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Observation fe425793-ced8-48fb-af73-dc0a56e880a2 · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library,.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images Pytorch: An imperative style, high-performance deep learning library,

Reference 35

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Observation 93b498db-5c1f-4c28-a88f-c37f7c80352a · outbound

This paper cites Mumford–shah loss functional for image seg- mentation with deep learning,.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images Mumford–shah loss functional for image seg- mentation with deep learning,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:29:12.643088Z

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Observation 75bf56a2-1995-449f-91fe-f654304eae36 · outbound

This paper cites Na- sopharyngeal carcinoma segmentation based on enhanced convolutional neural networks using multi-modal metric learning,.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images Na- sopharyngeal carcinoma segmentation based on enhanced convolutional neural networks using multi-modal metric learning,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:29:12.395620Z

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Observation e9574e8e-9a42-420c-8c0b-4d357747b3ed · outbound

This paper cites Road extraction by deep residual u- net,.

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images Road extraction by deep residual u- net,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:29:12.129526Z

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