Paper Citation Record · LEDGER

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels

As of 22 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2501.06678.

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pith.paper-citation-record.v1
2501.06678 v1

Coverage vector

measured 37 of 37 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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

Source: cited_works

Reference resolution

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External citation measurements

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Outbound references

Observation 588c0a94-181e-4119-a03b-d2d9f2009aae · outbound

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

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Generalizing deep learning for medical image segmentation to unseen domains via deep stacked transformation,

Reference 1

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Observation cd911b3d-6be8-4087-aaa3-9a242ab68dbb · outbound

This paper cites Retinal vessel segmen- tation with skeletal prior and contrastive loss,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Retinal vessel segmen- tation with skeletal prior and contrastive loss,

Reference 2

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Observation a83b0a1e-18c2-454a-bc0a-446225c64201 · outbound

This paper cites Joint class-affinity loss correction for robust medi- cal image segmentation with noisy labels,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Joint class-affinity loss correction for robust medi- cal image segmentation with noisy labels,

Reference 3

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Observation 6bbe3902-e6a4-4589-9667-fe9378ba4ecc · outbound

This paper cites Superpixel-guided iterative learning from noisy labels for medical image segmentation,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Superpixel-guided iterative learning from noisy labels for medical image segmentation,

Reference 4

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Observation e01b9bca-909a-477f-8fdf-947a5c292741 · outbound

This paper cites A closer look at memorization in deep networks,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels A closer look at memorization in deep networks,

Reference 5

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Observation f2e34fa3-f326-4b05-8ecb-f9daa2f8ce86 · outbound

This paper cites Does label smoothing mitigate label noise?,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Does label smoothing mitigate label noise?,

Reference 6

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Observation f94f2354-c85f-4cef-94ac-0ede97a94821 · outbound

This paper cites Are anchor points really indispensable in label-noise learning?,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Are anchor points really indispensable in label-noise learning?,

Reference 7

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Observation 1e7f8f8b-4df3-4cee-b6be-8e402ca6dd65 · outbound

This paper cites Provably end-to-end label-noise learning without anchor points,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Provably end-to-end label-noise learning without anchor points,

Reference 8

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Observation cfcc878f-e664-44e6-9ebb-46b745c9e5d6 · outbound

This paper cites Co-teaching: Robust training of deep neural networks with extremely noisy labels,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Co-teaching: Robust training of deep neural networks with extremely noisy labels,

Reference 9

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Observation 7f1fcc32-99c5-4282-8be0-6d810aaf07a4 · outbound

This paper cites Review–a survey of learning from noisy labels,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Review–a survey of learning from noisy labels,

Reference 10

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Observation 0576807f-e163-4d24-b72b-04e959aa7505 · outbound

This paper cites Augmentation strategies for learning with noisy labels,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Augmentation strategies for learning with noisy labels,

Reference 11

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Observation ad21a0b9-3e2c-48e1-ba3a-f978777c33d5 · outbound

This paper cites Iterative learning with open-set noisy labels,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Iterative learning with open-set noisy labels,

Reference 12

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This paper cites Combating noisy labels by agree- ment: A joint training method with co-regularization,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Combating noisy labels by agree- ment: A joint training method with co-regularization,

Reference 13

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Observation 1e9203ef-9fc6-4d08-82ac-3461c9705566 · outbound

This paper cites Using trusted data to train deep networks on labels corrupted by severe noise,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Using trusted data to train deep networks on labels corrupted by severe noise,

Reference 14

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Observation c41936ff-325e-4dcc-b46e-74b0a365a1a4 · outbound

This paper cites Active bias: Training more accurate neural networks by emphasizing high variance samples,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Active bias: Training more accurate neural networks by emphasizing high variance samples,

Reference 15

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Observation 0f37e8c7-163b-46b9-a337-4fe2d27af58a · outbound

This paper cites Generalized cross entropy loss for training deep neural networks with noisy labels,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Generalized cross entropy loss for training deep neural networks with noisy labels,

Reference 16

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This paper cites A semi-supervised two-stage approach to learning from noisy labels,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels A semi-supervised two-stage approach to learning from noisy labels,

Reference 17

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Observation e03e21fc-42d8-4625-819d-40cb6a3c5059 · outbound

This paper cites Semi-supervised semantic segmentation with cross pseudo supervision,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Semi-supervised semantic segmentation with cross pseudo supervision,

Reference 18

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This paper cites Semi-supervised semantic segmen- tation with cross-consistency training,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Semi-supervised semantic segmen- tation with cross-consistency training,

Reference 19

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Observation 4e87b245-db15-48ba-a575-05402bf954fe · outbound

This paper cites Deep learning with noisy labels: Exploring techniques and remedies in medical image analysis,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Deep learning with noisy labels: Exploring techniques and remedies in medical image analysis,

Reference 20

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Observation b335dcf8-bd8c-41c4-95bd-90184dfb0819 · outbound

This paper cites When Source-Free Domain Adaptation Meets Learning with Noisy Labels.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels When Source-Free Domain Adaptation Meets Learning with Noisy Labels

Reference 21

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Observation 287c41a9-b58e-4ee7-b4e9-7393ff9973cc · outbound

This paper cites Characterizing label errors: confident learning for noisy-labeled image segmentation,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Characterizing label errors: confident learning for noisy-labeled image segmentation,

Reference 22

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This paper cites How does disagreement help generalization against label corruption?,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels How does disagreement help generalization against label corruption?,

Reference 23

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This paper cites Flexmatch: Boosting semi-supervised learning with curriculum pseudo labeling,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Flexmatch: Boosting semi-supervised learning with curriculum pseudo labeling,

Reference 24

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Observation 81c713d9-3fa2-4a9b-9283-6e0ad09ee79d · outbound

This paper cites Symmetric cross entropy for robust learning with noisy labels,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Symmetric cross entropy for robust learning with noisy labels,

Reference 25

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This paper cites Understanding and improving early stopping for learning with noisy labels,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Understanding and improving early stopping for learning with noisy labels,

Reference 26

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Observation 5e5ac582-3d91-4da2-a470-3a74eed9e149 · outbound

This paper cites Coresets for robust training of deep neural networks against noisy labels,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Coresets for robust training of deep neural networks against noisy labels,

Reference 27

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This paper cites Robustness of accuracy metric and its inspirations in learning with noisy labels,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Robustness of accuracy metric and its inspirations in learning with noisy labels,

Reference 28

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This paper cites Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs,

Reference 29

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This paper cites 2018 Robotic Scene Segmentation Challenge.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels 2018 Robotic Scene Segmentation Challenge

Reference 30

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This paper cites Isinet: an instance- based approach for surgical instrument segmentation,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Isinet: an instance- based approach for surgical instrument segmentation,

Reference 31

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Observation 2bdc8364-86e6-4b45-855d-e0edcf31a89f · outbound

This paper cites Agreement among ophthalmologists in marking the optic disc and optic cup in fundus images,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Agreement among ophthalmologists in marking the optic disc and optic cup in fundus images,

Reference 32

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Observation 2d835fd9-8de0-4058-acfa-20105d5c0ab4 · outbound

This paper cites 2017 Robotic Instrument Segmentation Challenge.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels 2017 Robotic Instrument Segmentation Challenge

Reference 33

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This paper cites Learning calibrated medical image segmentation via multi- rater agreement modeling,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Learning calibrated medical image segmentation via multi- rater agreement modeling,

Reference 34

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This paper cites Learning from noisy labels via discrepant collaborative training,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Learning from noisy labels via discrepant collaborative training,

Reference 35

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Observation 93fb3c62-122b-496f-8350-12be7d4a69d2 · outbound

This paper cites Adaptive early-learning correction for segmentation from noisy annotations,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Adaptive early-learning correction for segmentation from noisy annotations,

Reference 36

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Observation 53a86fe4-f777-4877-af8e-afb239524c4c · outbound

This paper cites Anti-interference from noisy labels: Mean-teacher-assisted confident learning for medical image segmentation,.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Anti-interference from noisy labels: Mean-teacher-assisted confident learning for medical image segmentation,

Reference 37

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Pith citing papers

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