Paper Citation Record · LEDGER

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation

As of 19 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 1 inbound Pith citation observation for arXiv:2502.05473.

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

pith.paper-citation-record.v1
2502.05473 v1

Coverage vector

measured 43 of 43 reference resolution

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-15T04:56:33.261444Z

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

Source: cited_works

Reference resolution

43 of 43 outbound references displayed

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External citation measurements

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Outbound references

Observation 3342dcaf-efff-4d9c-8283-9e31af703e29 · outbound

This paper cites A survey on medical image segmentation,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation A survey on medical image segmentation,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:18:03.502868Z

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Observation 65ec0add-2da3-47ce-a917-86eb352adb84 · outbound

This paper cites A deep learning-based auto-segmentation system for organs-at-risk on whole-body computed tomography images for radiation therapy,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation A deep learning-based auto-segmentation system for organs-at-risk on whole-body computed tomography images for radiation therapy,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:18:03.487323Z

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Observation 09a26cf7-c99e-488a-99d9-8c3732631e85 · outbound

This paper cites Concurrent multimodality image segmentation by active contours for radiotherapy treatment planning a,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Concurrent multimodality image segmentation by active contours for radiotherapy treatment planning a,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:18:03.472216Z

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Observation 34743d81-2066-4aa8-8d3b-374a4f0aa209 · outbound

This paper cites Segnet: A deep con- volutional encoder-decoder architecture for image segmentation,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Segnet: A deep con- volutional encoder-decoder architecture for image segmentation,

Reference 4

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Observation cda7c435-30a9-490a-81a1-4194efde87fe · outbound

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

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

Reference 5

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Observation 73951443-8259-4890-87d8-4b4f3bfc1544 · outbound

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

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation U-net: Convolutional networks for biomedical image segmentation,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:18:03.439638Z

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Observation 534b8b51-56e9-41c9-b6f1-f21057588eae · outbound

This paper cites Active contours without edges,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Active contours without edges,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:18:03.411917Z

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Observation 801285b8-7d82-46fc-a605-da3ed7269e66 · outbound

This paper cites A multiphase level set framework for image segmentation using the mumford and shah model,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation A multiphase level set framework for image segmentation using the mumford and shah model,

Reference 8

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Observation ba2c7c79-be32-4811-8df0-e8cc3b85ccbe · outbound

This paper cites Panet: Few-shot image semantic segmentation with prototype alignment,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Panet: Few-shot image semantic segmentation with prototype alignment,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:18:03.384135Z

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Observation 1f422a87-0ae9-4b73-997a-2c9f1b7be096 · outbound

This paper cites Flexisp: A flexible camera image processing framework,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Flexisp: A flexible camera image processing framework,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:18:03.368587Z

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Observation ecbb973c-459c-4360-86a2-c8f3f7e9d984 · outbound

This paper cites Learned primal-dual reconstruction,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Learned primal-dual reconstruction,

Reference 11

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Observation 97a69908-0911-4fcf-9b7d-998114d6cdc6 · outbound

This paper cites A first-order primal-dual algorithm for convex problems with applications to imaging,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation A first-order primal-dual algorithm for convex problems with applications to imaging,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:18:03.337986Z

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Observation 9ef367a1-6c79-4af7-bc09-21acb4988a85 · outbound

This paper cites Optimal approximations by piecewise smooth functions and associated variational problems,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Optimal approximations by piecewise smooth functions and associated variational problems,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:18:03.320014Z

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Observation c1ca63c6-8bd5-4d31-8c60-2426eb54dbcf · outbound

This paper cites Ista-net: Interpretable optimization-inspired deep network for image compressive sensing,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Ista-net: Interpretable optimization-inspired deep network for image compressive sensing,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:18:03.304014Z

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Observation 85aff2a1-2de5-4551-a38a-a800f66aeb46 · outbound

This paper cites Admm-csnet: A deep learning approach for image compressive sensing,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Admm-csnet: A deep learning approach for image compressive sensing,

Reference 15

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Observation 51c89633-a236-49e6-bc21-388a83b8958f · outbound

This paper cites Nonlocal regularized cnn for image segmentation,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Nonlocal regularized cnn for image segmentation,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:18:03.272336Z

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Observation 3e43a2a0-1cdb-4a6a-b3b8-d991cbb87185 · outbound

This paper cites Deep convolutional neural networks with spatial regularization, volume and star-shape priors for image segmentation,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Deep convolutional neural networks with spatial regularization, volume and star-shape priors for image segmentation,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:18:03.254411Z

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Observation 2db1333d-c564-4f72-92df-9946079f1fd1 · outbound

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LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Unresolved cited work

Reference 18

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Observation 58f2539a-c73a-4cd9-8962-58991d06420d · outbound

This paper cites Assembling a learnable mumford–shah type model with multigrid technique for image segmen- tation,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Assembling a learnable mumford–shah type model with multigrid technique for image segmen- tation,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:18:03.238110Z

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Observation 13fabf41-d2f8-4ab2-9d45-cc0104d3835d · outbound

This paper cites Global minimization for continuous multiphase partitioning problems using a dual approach,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Global minimization for continuous multiphase partitioning problems using a dual approach,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:18:03.220992Z

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Observation a6dd1ff4-6a90-4e60-98fa-bf40ab8ef714 · outbound

This paper cites Denoising prior driven deep neural network for image restoration,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Denoising prior driven deep neural network for image restoration,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:18:03.204531Z

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Observation 65ba9d8f-a7dc-4b0b-b585-70609f325866 · outbound

This paper cites Deep unfolding network for image super-resolution,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Deep unfolding network for image super-resolution,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:18:03.187732Z

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Observation e362e34f-a98f-4d51-b530-9a42fe9ab3e0 · outbound

This paper cites Cpp-net: Embracing multi-scale feature fusion into deep unfolding cp-ppa network for compressive sensing,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Cpp-net: Embracing multi-scale feature fusion into deep unfolding cp-ppa network for compressive sensing,

Reference 23

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Observation 92a06311-d6fa-4e0e-a9b5-82fe6d8ef141 · outbound

This paper cites A multiphase image segmentation method based on fuzzy region competition,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation A multiphase image segmentation method based on fuzzy region competition,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:18:03.159287Z

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Observation 634a5628-5759-4725-956f-2b591a92da96 · outbound

This paper cites Trainable nonlinear reaction diffusion: A flexible framework for fast and effective image restoration,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Trainable nonlinear reaction diffusion: A flexible framework for fast and effective image restoration,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:18:03.088199Z

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Observation 5048f72f-91e5-4019-841b-2897020b625c · outbound

This paper cites Unfolded proximal neural networks for robust image gaussian denoising,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Unfolded proximal neural networks for robust image gaussian denoising,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:18:03.040525Z

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Observation 6e060b55-2e1f-4178-91ce-78b28cbedd98 · outbound

This paper cites Some generalized order-disorder transformations,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Some generalized order-disorder transformations,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:18:03.018882Z

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Observation 0f85baaf-a5cc-44f5-838f-976b9d1ceda3 · outbound

This paper cites Signal recovery by proximal forward- backward splitting,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Signal recovery by proximal forward- backward splitting,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:18:02.996547Z

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Observation ef8e9753-9357-4f53-8a3c-aa7ed948d16e · outbound

This paper cites Proximité et dualité dans un espace hilbertien,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Proximité et dualité dans un espace hilbertien,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:18:02.975553Z

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Observation 1b894a32-bb33-4776-b062-f0565b702a36 · outbound

This paper cites Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-08T19:18:02.656394Z

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Observation 00a1b08d-d01c-479c-9b9c-f34b26bdf1e0 · outbound

This paper cites Few-shot semantic segmentation with proto- type learning.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Few-shot semantic segmentation with proto- type learning

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:18:02.950018Z

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Observation b6ea00a8-165a-4fa4-af9b-c15d41b85a8b · outbound

This paper cites Few-shot medical image segmentation via a region-enhanced prototypical transformer,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Few-shot medical image segmentation via a region-enhanced prototypical transformer,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:18:02.932756Z

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Observation 960aa7a2-d0b8-42ae-b3e9-7111cc0fd8e8 · outbound

This paper cites Anomaly detection-inspired few-shot medical image segmentation through self- supervision with supervoxels,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Anomaly detection-inspired few-shot medical image segmentation through self- supervision with supervoxels,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:18:02.917558Z

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Observation a708515e-bca2-46ec-8627-8b4a47f845c4 · outbound

This paper cites Intermediate prototype mining transformer for few-shot semantic segmentation,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Intermediate prototype mining transformer for few-shot semantic segmentation,

Reference 34

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Observation 720a2973-cbdb-4b32-a66f-7139866386a3 · outbound

This paper cites Self- supervision with superpixels: Training few-shot medical image seg- mentation without annotation,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Self- supervision with superpixels: Training few-shot medical image seg- mentation without annotation,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:18:02.890164Z

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Observation 60ea553b-0043-432d-9902-40b249956897 · outbound

This paper cites Rethinking few-shot medical segmentation: a vector quantization view,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Rethinking few-shot medical segmentation: a vector quantization view,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:18:02.872556Z

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Observation 41e2f7a1-6d12-4f7c-bc80-0f17fd9e3b61 · outbound

This paper cites Recurrent mask refinement for few-shot medical image segmentation,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Recurrent mask refinement for few-shot medical image segmentation,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:18:02.857149Z

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Observation 0247f02a-1794-49ab-85d8-a2c508aae2c2 · outbound

This paper cites Miccai multi-atlas labeling beyond the cranial vault–workshop and challenge,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Miccai multi-atlas labeling beyond the cranial vault–workshop and challenge,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:18:02.840496Z

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Observation 632f4c34-7021-4c4b-9407-f3d0110737bc · outbound

This paper cites Chaos challenge- combined (ct-mr) healthy abdominal organ segmentation,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Chaos challenge- combined (ct-mr) healthy abdominal organ segmentation,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:18:02.825390Z

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Observation ea8f6534-4826-4d0a-b2cc-b8e73a0f0702 · outbound

This paper cites Multivariate mixture model for myocardial segmentation combining multi-source images,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Multivariate mixture model for myocardial segmentation combining multi-source images,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:18:02.809592Z

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Observation de5ee809-a081-4313-b9de-4e56f7959a61 · outbound

This paper cites Deep residual learning for image recognition,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Deep residual learning for image recognition,

Reference 41

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Observation c34c0d6b-8962-4770-848e-9693eb6c88fc · outbound

This paper cites Microsoft coco: Common objects in context,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Microsoft coco: Common objects in context,

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-08T19:18:02.711648Z

Source-reported events for the cited work

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Observation 3df4969f-7595-4529-9797-720fd3db9936 · outbound

This paper cites Large-scale machine learning with stochastic gradient de- scent,.

LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation Large-scale machine learning with stochastic gradient de- scent,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:18:02.772621Z

Source-reported events for the cited work

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Pith citing papers

Observation c99bea82-1a0c-454c-a30e-32ea18d08591 · inbound

Medical Image Segmentation based on Deep Active Contour and Mean Curvature Loss Function cites this paper.

Medical Image Segmentation based on Deep Active Contour and Mean Curvature Loss Function LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-15T04:56:33.261444Z

Source-reported events for the cited work

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