Paper Citation Record · LEDGER

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation

As of 12 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 2 inbound Pith citation observations for arXiv:2502.06650.

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

pith.paper-citation-record.v1
2502.06650 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T14:51:20.261727Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T10:53:48.721067Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-09T21:46:34.606389Z

Reference resolution

41 of 41 outbound references displayed

verified exact1
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 982070eb-2cab-4528-9d3d-0440d33e6733 · outbound

This paper cites Fully convolutional networks for semantic segmentation.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Fully convolutional networks for semantic segmentation

Reference 1

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Observation f858650a-4a1a-44e1-85d6-2cda5ce510fe · outbound

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

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation U-net: Convolutional networks for biomedical image segmentation

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.811964Z

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Observation ddedea40-cf25-4b17-8b93-77b4d3be1eec · outbound

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

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation 3d u-net: learning dense volumetric segmentation from sparse annotation

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.797528Z

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Observation c953772a-0384-45ef-a404-c8e9ddbb8bc6 · outbound

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

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation V-net: Fully convolutional neural networks for volumetric medical image segmentation

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.783836Z

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Observation efab2d43-612e-4806-937d-5db5ba2faa90 · outbound

This paper cites Unet++: Redesigning skip connections to exploit multiscale features in image segmentation.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Unet++: Redesigning skip connections to exploit multiscale features in image segmentation

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.770090Z

Source-reported events for the cited work

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Observation 30844b86-f715-4cc9-a586-12a87ec9f586 · outbound

This paper cites Rethinking Atrous Convolution for Semantic Image Segmentation.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Rethinking Atrous Convolution for Semantic Image Segmentation

Reference 6

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Observation 0847bd17-908a-41b8-a41c-1469c4db29d9 · outbound

This paper cites Deep high-resolution representation learning for human pose estimation.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Deep high-resolution representation learning for human pose estimation

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.756477Z

Source-reported events for the cited work

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Observation 2a5790bb-139d-442b-9178-b36dc59dc3b5 · outbound

This paper cites Deep co-training for semi-supervised image segmentation.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Deep co-training for semi-supervised image segmentation

Reference 8

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Observation 498cae3e-3c17-462e-9140-c872e8b063c4 · outbound

This paper cites Semi-supervised left atrium segmentation with mutual consistency training.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Semi-supervised left atrium segmentation with mutual consistency training

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.734740Z

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Observation b4d35a09-99ee-48bf-9f6c-837b0254431d · outbound

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

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Semi-supervised semantic segmentation with cross pseudo supervision

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.721569Z

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Observation dc81e53c-d4df-41e4-a499-1d231a0ec569 · outbound

This paper cites Advent: Adversarial entropy minimization for domain adaptation in semantic segmentation.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Advent: Adversarial entropy minimization for domain adaptation in semantic segmentation

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.709793Z

Source-reported events for the cited work

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Observation 412329fa-f935-413c-80c4-0126abb2ea02 · outbound

This paper cites Momentum contrast for unsupervised visual representation learning.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Momentum contrast for unsupervised visual representation learning

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.698065Z

Source-reported events for the cited work

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Observation 0a490f6b-056f-4a5b-bf80-2505cc20903d · outbound

This paper cites A simple framework for contrastive learning of visual representations.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation A simple framework for contrastive learning of visual representations

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.686264Z

Source-reported events for the cited work

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Observation 1a2f39c8-4e26-40e4-b408-9e8f32ce7f54 · outbound

This paper cites Contrastive learning of global and local features for medical image segmentation with limited annotations.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Contrastive learning of global and local features for medical image segmentation with limited annotations

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.673085Z

Source-reported events for the cited work

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Observation b32866d2-395f-4e23-ad99-ad6ad678c515 · outbound

This paper cites Exploring cross-image pixel contrast for semantic segmentation.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Exploring cross-image pixel contrast for semantic segmentation

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.659578Z

Source-reported events for the cited work

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Observation 9a7145fa-9624-4cbf-a94f-ff5e3ffd4e17 · outbound

This paper cites Pixel contrastive-consistent semi-supervised semantic segmentation.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Pixel contrastive-consistent semi-supervised semantic segmentation

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.646217Z

Source-reported events for the cited work

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Observation a5449e8e-f446-41e2-8578-3700cd54b631 · outbound

This paper cites Semi-supervised contrastive learning for label-efficient medical image segmentation.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Semi-supervised contrastive learning for label-efficient medical image segmentation

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.632816Z

Source-reported events for the cited work

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Observation e043b77e-bfaa-41f4-9339-1a33ec82e6f6 · outbound

This paper cites Uncertainty-guided pixel contrastive learning for semi-supervised medical image segmentation.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Uncertainty-guided pixel contrastive learning for semi-supervised medical image segmentation

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.619493Z

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Observation 229dd31d-fe07-47ce-9cc7-40c20deb0d63 · outbound

This paper cites Semi-supervised semantic segmentation using unreliable pseudo-labels.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Semi-supervised semantic segmentation using unreliable pseudo-labels

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.606446Z

Source-reported events for the cited work

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Observation 61454e3c-d87e-4283-8d81-c189b97a75dd · outbound

This paper cites Semi-supervised medical image segmentation via a tripled-uncertainty guided mean teacher model with contrastive learning.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Semi-supervised medical image segmentation via a tripled-uncertainty guided mean teacher model with contrastive learning

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.592526Z

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Observation a49d6a71-1eb4-4ed9-8d36-e6edb44a56a1 · outbound

This paper cites Rethinking semantic segmentation: A prototype view.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Rethinking semantic segmentation: A prototype view

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.577618Z

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Observation 7da55d31-7d43-46fd-b439-7cc186b5b176 · outbound

This paper cites Semi-supervised semantic segmentation via prototypical contrastive learning.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Semi-supervised semantic segmentation via prototypical contrastive learning

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.564398Z

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Observation 3bcf084e-96ba-40b4-841e-c9cb7a50b993 · outbound

This paper cites Self-aware and cross-sample prototypical learning for semi-supervised medical image segmentation.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Self-aware and cross-sample prototypical learning for semi-supervised medical image segmentation

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.551239Z

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Observation e437f2f6-27a2-45a1-a245-dc68b655799b · outbound

This paper cites Improved Baselines with Momentum Contrastive Learning.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Improved Baselines with Momentum Contrastive Learning

Reference 24

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Observation d71bf89f-834c-489c-bd43-9b4d78b6d6ae · outbound

This paper cites Region-level Contrastive and Consistency Learning for Semi-Supervised Semantic Segmentation.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Region-level Contrastive and Consistency Learning for Semi-Supervised Semantic Segmentation

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-08-08T14:51:20.316336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 59a7fe16-0160-4b75-885b-9e16aa3342b1 · outbound

This paper cites Local contrastive loss with pseudo-label based self-training for semi-supervised medical image segmentation.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Local contrastive loss with pseudo-label based self-training for semi-supervised medical image segmentation

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.538047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 05741085-2dae-4ac3-8105-8dc39f2b797f · outbound

This paper cites Deep co-training for semi-supervised image recognition.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Deep co-training for semi-supervised image recognition

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.524801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 2d107b69-a747-46d2-bb75-e9af1465fe21 · outbound

This paper cites Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results

Reference 28

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Observation 8afe1e75-37c4-48ff-87c7-d2a82bd0ccfd · outbound

This paper cites Uncertainty-aware self-ensembling model for semi-supervised 3d left atrium segmentation.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Uncertainty-aware self-ensembling model for semi-supervised 3d left atrium segmentation

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.503558Z

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Observation efdc7cfb-0608-4570-ad29-fc88e75861b0 · outbound

This paper cites Transformation-consistent self-ensembling model for semisupervised medical image segmentation.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Transformation-consistent self-ensembling model for semisupervised medical image segmentation

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.490082Z

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Observation 3ac8ab1e-7b46-4905-bcd7-e2e8c075f7db · outbound

This paper cites Deep adversarial networks for biomedical image segmentation utilizing unannotated images.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Deep adversarial networks for biomedical image segmentation utilizing unannotated images

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.478044Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 60ebf46a-42dd-445c-b77c-d39133530ed6 · outbound

This paper cites Temporal Ensembling for Semi-Supervised Learning.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Temporal Ensembling for Semi-Supervised Learning

Reference 32

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Observation 283fe22f-281d-436c-99e0-10d55a20e670 · outbound

This paper cites Efficient semi-supervised gross target volume of nasopharyngeal carcinoma segmentation via uncertainty rectified pyramid consistency.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Efficient semi-supervised gross target volume of nasopharyngeal carcinoma segmentation via uncertainty rectified pyramid consistency

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.465895Z

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Observation 68af6d72-c084-434b-8e12-427dac0ba29d · outbound

This paper cites Semi-supervised medical image segmentation through dual-task consistency.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Semi-supervised medical image segmentation through dual-task consistency

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.452305Z

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Observation eb555d4b-2d98-4ed9-ac06-47d2e29092b2 · outbound

This paper cites Shape-aware semi-supervised 3d semantic segmentation for medical images.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Shape-aware semi-supervised 3d semantic segmentation for medical images

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.439000Z

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Observation 2c96c0ed-9c56-4062-8e49-6205d3797b2d · outbound

This paper cites Dataset of breast ultrasound images.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Dataset of breast ultrasound images

Reference 36

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Observation 18127851-9769-40a6-8211-aa148f725440 · outbound

This paper cites Deep learning techniques for automatic mri cardiac multi-structures segmentation and diagnosis: is the problem solved? IEEE Transactions on Medical Imaging, 37:2514–2525, 2018.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Deep learning techniques for automatic mri cardiac multi-structures segmentation and diagnosis: is the problem solved? IEEE Transactions on Medical Imaging, 37:2514–2525, 2018

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.415628Z

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Observation fbff4b7f-6b1f-4564-af91-6b47e7a9797c · outbound

This paper cites Semi-supervised semantic segmentation with cross-consistency training.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Semi-supervised semantic segmentation with cross-consistency training

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.401287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ac33264a-91e6-4b05-afee-f9f469659e3e · outbound

This paper cites Exploring smoothness and class-separation for semi-supervised medical image segmentation.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Exploring smoothness and class-separation for semi-supervised medical image segmentation

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.387318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation dfcecce4-6db6-4c7e-bdba-80314517a036 · outbound

This paper cites Semi-supervised medical image segmentation using cross-model pseudo-supervision with shape awareness and local context constraints.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Semi-supervised medical image segmentation using cross-model pseudo-supervision with shape awareness and local context constraints

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.373401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d1207cff-91a2-4bf2-9578-f93eefed485a · outbound

This paper cites Self-aware and cross-sample prototypical learning for semi-supervised medical image segmentation.

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation Self-aware and cross-sample prototypical learning for semi-supervised medical image segmentation

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:51:20.358950Z

Source-reported events for the cited work

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Pith citing papers

Observation a4982bf7-3e5e-4441-9c2d-203a92baa1af · inbound

AGA: An adaptive group alignment framework for structured medical cross-modal representation learning cites this paper.

AGA: An adaptive group alignment framework for structured medical cross-modal representation learning Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation

Reference 14

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Observation 3fe031ce-3201-4569-aff4-3e29e04411f5 · inbound

SHTA: Semantic Hard Token Correction and Center Alignment for Semi-Supervised Medical Image Segmentation cites this paper.

SHTA: Semantic Hard Token Correction and Center Alignment for Semi-Supervised Medical Image Segmentation Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-07-09T21:46:34.607780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.