Paper Citation Record · LEDGER

Pixel-wise Modulated Dice Loss for Medical Image Segmentation

As of 9 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 2 inbound Pith citation observations for arXiv:2506.15744.

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

pith.paper-citation-record.v1
2506.15744 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:14:33.496694Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T12:55:49.697340Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T07:12:28.060743Z

Reference resolution

47 of 47 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d9ae5941-9651-4e73-894e-a6349504d986 · outbound

This paper cites Loss odyssey in medical image segmentation.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Loss odyssey in medical image segmentation

Reference 1

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Observation a6a7511d-79a5-42a7-97cc-3958811ec0bb · outbound

This paper cites Focal loss for dense object detection.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Focal loss for dense object detection

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:41.886101Z

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Observation 5c7387aa-2b30-4300-aae9-cc15d351d3f9 · outbound

This paper cites Full-resolution residual ne tworks for semantic segmentation in street scenes.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Full-resolution residual ne tworks for semantic segmentation in street scenes

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:41.710382Z

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Observation 1496b53d-19a1-4acf-a524-55250f550fac · outbound

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

Pixel-wise Modulated Dice Loss for Medical Image Segmentation U- net: Convolutional networks for biomedical image segmentation

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:41.564324Z

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Observation af0c5129-38b9-4eb4-93f5-a25a19a1926c · outbound

This paper cites Optimizing the dice score and jaccard index for medical image segmentation: Theory and practice.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Optimizing the dice score and jaccard index for medical image segmentation: Theory and practice

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:41.424105Z

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Observation 56ae1074-7883-417a-b6b7-1cc307736624 · outbound

This paper cites Deep residual learning for ima ge recognition.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Deep residual learning for ima ge recognition

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:41.228491Z

Source-reported events for the cited work

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Observation 1b1ea7a1-2308-420c-b7d3-64405772b03f · outbound

This paper cites FCB-SwinV2 Transformer for Polyp Segmentation.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation FCB-SwinV2 Transformer for Polyp Segmentation

Reference 7

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Observation eb397ce6-fb6d-41a8-a15a-111cc1ded351 · outbound

This paper cites Kvasir-SEG: A Segmented Polyp Dataset,.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Kvasir-SEG: A Segmented Polyp Dataset,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:41.056735Z

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Observation 6281d25d-1672-4f55-a482-42829667c079 · outbound

This paper cites WM-DOVA maps for accurate polyp highlighting in colonoscopy: Validat ion vs. saliency maps from physicians,.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation WM-DOVA maps for accurate polyp highlighting in colonoscopy: Validat ion vs. saliency maps from physicians,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:40.877984Z

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Observation d46be422-b5fc-4780-8221-1577df93b3cb · outbound

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

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)

Reference 10

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Observation a466a688-84e1-4944-a3b1-d90e2475436e · outbound

This paper cites In: International Confere nce on Medical Image Computing and Computer-Assisted Intervention.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation In: International Confere nce on Medical Image Computing and Computer-Assisted Intervention

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:40.626378Z

Source-reported events for the cited work

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Observation 6390e74b-3277-4947-ba7a-209651f2fea2 · outbound

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

Pixel-wise Modulated Dice Loss for Medical Image Segmentation TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

Reference 12

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Observation c948f1d5-d52f-4bee-9d04-e8da94023081 · outbound

This paper cites Pranet: Parallel reverse at tention network for polyp segmentation.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Pranet: Parallel reverse at tention network for polyp segmentation

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:40.464660Z

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Observation 9c297095-b9e7-45dd-97f1-0e3ec6e30b32 · outbound

This paper cites Uacanet: Uncertainty augmented context attention for polyp segmentation.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Uacanet: Uncertainty augmented context attention for polyp segmentation

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:40.307453Z

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Observation 8243d506-0cb7-4dea-8577-c7b781e8b82c · outbound

This paper cites nnU-Net for brain tumor segmentation.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation nnU-Net for brain tumor segmentation

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:40.175537Z

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Observation 6395c656-9f84-45f4-9b6a-f91975b92073 · outbound

This paper cites Multi-scale Hierarchical Vision Transformer with Cascaded Attention Decoding for Medical Image Segmentation.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Multi-scale Hierarchical Vision Transformer with Cascaded Attention Decoding for Medical Image Segmentation

Reference 16

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Observation 2a56d6bb-5f73-4ed0-838d-09363f5b6e8e · outbound

This paper cites Class-balanced loss based on eff ective number of samples.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Class-balanced loss based on eff ective number of samples

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:40.119299Z

Source-reported events for the cited work

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Observation 8680f1f8-1bf7-4e03-a892-0de2dc8a57a0 · outbound

This paper cites In Proceedings of the IEEE international conference on computer vision, p ages 1395–1403, 2015.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation In Proceedings of the IEEE international conference on computer vision, p ages 1395–1403, 2015

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:39.834750Z

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Observation 6f1eb4fd-4f02-4750-b7a0-7494b95001e4 · outbound

This paper cites Universal loss reweightin g to balance lesion size inequality in 3D medical image segmentation.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Universal loss reweightin g to balance lesion size inequality in 3D medical image segmentation

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:39.532199Z

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Observation bb940e68-ede0-4424-9289-593c502f2e94 · outbound

This paper cites Learning from imbalanced data.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Learning from imbalanced data

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:39.265612Z

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Observation 8d65a0f7-194d-4a19-9bc9-d22bad32d194 · outbound

This paper cites Rethinking Atrous Convolution for Semantic Image Segmentation.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Rethinking Atrous Convolution for Semantic Image Segmentation

Reference 21

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Observation 089db6d0-cc4c-47ae-8f62-2b68df892e85 · outbound

This paper cites Generalised dice overlap as a deep learning loss function for highly unbalanced segmentations.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Generalised dice overlap as a deep learning loss function for highly unbalanced segmentations

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:38.925433Z

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Observation c384bde4-8b60-4532-a09d-e3c51e04f33e · outbound

This paper cites Tversky loss function for image segment ation using 3D fully convolutional deep networks.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Tversky loss function for image segment ation using 3D fully convolutional deep networks

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:38.546279Z

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Observation 8458af71-39cd-4c32-ac7d-e72f6e1aad20 · outbound

This paper cites Combo loss: Handling input and output imbalance in multi-organ segmentation.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Combo loss: Handling input and output imbalance in multi-organ segmentation

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:38.347569Z

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Observation d77f974b-82c1-4fa7-a3fd-03dd4757ece4 · outbound

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

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Unet++: Redesigning skip connections to exploit multiscale features in image segmentation

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:38.177244Z

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Observation a18c00ba-29dd-4d75-8f64-678ae61890ad · outbound

This paper cites Class-wise difficulty-balanced loss for solving cl ass- imbalance.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Class-wise difficulty-balanced loss for solving cl ass- imbalance

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:37.967462Z

Source-reported events for the cited work

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Observation 931040d1-4958-45fe-896a-ce60390c46e9 · outbound

This paper cites Bridging Category-level and Instance-level Semantic Image Segmentation.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Bridging Category-level and Instance-level Semantic Image Segmentation

Reference 27

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This paper cites Learning deep representation f or imbalanced classification.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Learning deep representation f or imbalanced classification

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:37.665671Z

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Observation 018d1e52-81fe-49fd-b0c2-6111d940ebd3 · outbound

This paper cites Automated volumetric assessment w ith artificial neural networks might enable a more accu rate assessment of disease burden in patients with multi ple sclerosis.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Automated volumetric assessment w ith artificial neural networks might enable a more accu rate assessment of disease burden in patients with multi ple sclerosis

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:37.449977Z

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Observation d0ea242a-18a0-4d9d-a1b8-53224438c14d · outbound

This paper cites Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy

Reference 30

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Observation 2c223048-3fd6-4bc9-9163-fa15c923bd06 · outbound

This paper cites Common Limitations of Image Processing Metrics: A Picture Story.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Common Limitations of Image Processing Metrics: A Picture Story

Reference 31

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Observation 92c3758c-d7a2-4d5e-9c37-0d4682a4a534 · outbound

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

Pixel-wise Modulated Dice Loss for Medical Image Segmentation V-net: Fully convolutional neural networks for vol umetric medical image segmentation

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:37.199651Z

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Observation 0a6c90a8-3e1b-4852-b941-e50da12fbb27 · outbound

This paper cites Balancing the Scales: A Comprehensive Study on Tackling Class Imbalance in Binary Classification.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Balancing the Scales: A Comprehensive Study on Tackling Class Imbalance in Binary Classification

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T00:14:32.187326Z

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Observation 4474f669-2546-42eb-bfe8-c370fbfcf1c4 · outbound

This paper cites SMOTE: synthetic minority over ‐ sampling technique.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation SMOTE: synthetic minority over ‐ sampling technique

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:36.882163Z

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Observation 6607ecb8-1c16-42fa-a3d1-ad4ff4c85153 · outbound

This paper cites One-Class Classification: A Survey.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation One-Class Classification: A Survey

Reference 35

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Observation da0c0119-3f6c-4b38-9385-099ff4ca0050 · outbound

This paper cites Handling imbalanced medical image data: A deep-learning-based one-class classification approach.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Handling imbalanced medical image data: A deep-learning-based one-class classification approach

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:36.472919Z

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Observation af84c281-19c3-49d5-ad8a-74b9a86393f4 · outbound

This paper cites Handling imbalanced medica l datasets: review of a decade of research.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Handling imbalanced medica l datasets: review of a decade of research

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:36.107375Z

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Observation 22b2a2e8-028d-4948-a9ce-2fe4b2401732 · outbound

This paper cites 3D segmentation with exponent ial logarithmic loss for highly unbalanced object sizes.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation 3D segmentation with exponent ial logarithmic loss for highly unbalanced object sizes

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:35.755275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9ce81980-5c22-428e-8f21-d11bc6f659a3 · outbound

This paper cites Focal dice loss and image dilation for brain tumor segmentation.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Focal dice loss and image dilation for brain tumor segmentation

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:35.576539Z

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Observation 6b9d2343-4b27-4008-b03b-8e86dfba72a2 · outbound

This paper cites Focal dice loss-based V-Net for liver segments classification.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Focal dice loss-based V-Net for liver segments classification

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:35.395405Z

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Observation 4af6bc5e-5928-4f42-9c54-65460b2e7730 · outbound

This paper cites Rethinking dice loss for me dical image segmentation.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Rethinking dice loss for me dical image segmentation

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:35.195214Z

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Observation e1a49687-1afe-49d1-896b-4fbfffdb441d · outbound

This paper cites topK dice loss for medical image segmentation.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation topK dice loss for medical image segmentation

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:35.042067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 14068624-3639-4da3-99b3-113f8334f90e · outbound

This paper cites In: Multimedia Modeling: 26th Internationa l Conference, MMM (2020).

Pixel-wise Modulated Dice Loss for Medical Image Segmentation In: Multimedia Modeling: 26th Internationa l Conference, MMM (2020)

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:34.650537Z

Source-reported events for the cited work

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Observation fd9bd21a-6d59-436d-9477-eedfc47966e3 · outbound

This paper cites Deep learning techniques for automatic MRI cardiac multi-structures segmentation and diagnosis: is the problem solved?.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Deep learning techniques for automatic MRI cardiac multi-structures segmentation and diagnosis: is the problem solved?

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:34.393783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2317907c-c806-4179-af16-9cda073f8be4 · outbound

This paper cites MSSEG-2 challenge proceedings: Multiple sclerosis new lesions segment ation challenge using a data management and processing infrastructure.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation MSSEG-2 challenge proceedings: Multiple sclerosis new lesions segment ation challenge using a data management and processing infrastructure

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:34.159507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 03adfeac-ff17-4208-a909-b39c135ade8c · outbound

This paper cites Double encoder-decoder networks for gastrointestinal polyp segmentation.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Double encoder-decoder networks for gastrointestinal polyp segmentation

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:33.823345Z

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Observation 6dfc349e-1209-4857-bd6d-21bd8b9c0213 · outbound

This paper cites Glasgow, UK, November 25-28, 2024.

Pixel-wise Modulated Dice Loss for Medical Image Segmentation Glasgow, UK, November 25-28, 2024

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:14:34.916707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Pith citing papers

Observation 6fc6d3eb-4ca1-450a-9dc7-7aeabc0082d2 · inbound

SEMIR: Semantic Minor-Induced Representation Learning on Graphs for Visual Segmentation cites this paper.

SEMIR: Semantic Minor-Induced Representation Learning on Graphs for Visual Segmentation Pixel-wise Modulated Dice Loss for Medical Image Segmentation

Reference 78

Resolution: verified exact; arxiv_id, observed 2026-05-13T07:12:28.063720Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 916954bd-dea9-4ccb-b030-40a55f643dae · inbound

DAMamba-UNet3D: A Parameter-Efficient Mamba State Space U-Net with Dynamic Adaptive Scan for 3D Medical Image Segmentation cites this paper.

DAMamba-UNet3D: A Parameter-Efficient Mamba State Space U-Net with Dynamic Adaptive Scan for 3D Medical Image Segmentation Pixel-wise Modulated Dice Loss for Medical Image Segmentation

Reference 19

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Source-reported events for the cited work

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