Paper Citation Record · LEDGER

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies

As of 11 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 6 inbound Pith citation observations for arXiv:2412.19990.

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

pith.paper-citation-record.v1
2412.19990 v2

Coverage vector

measured 54 of 54 reference resolution

Typed states for the displayed outbound observations.

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measured 60 of 60 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:32:05.186019Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T05:41:02.378249Z

Reference resolution

54 of 54 outbound references displayed

verified exact4
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c6591970-6e3e-4d2d-897a-186fe6ab8513 · outbound

This paper cites Bhsd: A 3d multi-class brain hemorrhage segmentation dataset,.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies Bhsd: A 3d multi-class brain hemorrhage segmentation dataset,

Reference 1

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Observation d8e75a41-bf53-4d70-b3d7-7f17d63bcdf1 · outbound

This paper cites Computational methods for liver vessel segmentation in medical imaging: A review,.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies Computational methods for liver vessel segmentation in medical imaging: A review,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:45:31.758584Z

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Observation d60ee232-97a4-4931-b1d0-4b142a1eb1da · outbound

This paper cites Deep learning: new computational modelling techniques for genomics,.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies Deep learning: new computational modelling techniques for genomics,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:45:31.743024Z

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Observation fd14cb1b-7584-457c-b077-803d2006f2f0 · outbound

This paper cites Deep learning modelling techniques: current progress, applications, advantages, and challenges,.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies Deep learning modelling techniques: current progress, applications, advantages, and challenges,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:45:31.727398Z

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Observation c7819beb-d2af-4f2b-b882-74b819224a28 · outbound

This paper cites A survey on deep learning: Algorithms, techniques, and applications,.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies A survey on deep learning: Algorithms, techniques, and applications,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:45:31.711252Z

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Observation b088d0ea-afff-46ab-a24b-752547361a11 · outbound

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

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies Chaos challenge-combined (ct-mr) healthy abdominal organ segmentation,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:45:31.696279Z

Source-reported events for the cited work

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Observation cbc75d8f-b9e6-46dc-9b05-512f00ef89e0 · outbound

This paper cites Abdomenct- 1k: Is abdominal organ segmentation a solved problem?,.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies Abdomenct- 1k: Is abdominal organ segmentation a solved problem?,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:45:31.675118Z

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Observation 4184dfb0-5f8c-4a9e-84bd-d9eb652b1c27 · outbound

This paper cites Cross- modal hybrid architectures for gastrointestinal tract image analysis: A systematic review and futuristic applications,.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies Cross- modal hybrid architectures for gastrointestinal tract image analysis: A systematic review and futuristic applications,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:45:31.657803Z

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Observation a209d309-2ae8-4833-be52-93728eff8f6c · outbound

This paper cites On the segmentation of vascular geometries from medical images,.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies On the segmentation of vascular geometries from medical images,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:45:31.642601Z

Source-reported events for the cited work

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Observation 22a56e33-d6bb-4d05-b084-b238769fa991 · outbound

This paper cites Laplacian salience- gated feature pyramid network for accurate liver vessel segmentation,.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies Laplacian salience- gated feature pyramid network for accurate liver vessel segmentation,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:45:31.626693Z

Source-reported events for the cited work

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Observation 1536ad16-39d9-4fb4-b2d6-baab26d3f844 · outbound

This paper cites Automated liver tissues delineation techniques: A systematic survey on machine learning current trends and future orientations,.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies Automated liver tissues delineation techniques: A systematic survey on machine learning current trends and future orientations,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:45:31.611028Z

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Observation 677e4bef-c85a-4b34-94a8-7b15fcc50e51 · outbound

This paper cites Review of liver segmentation and computer assisted detection/diagnosis methods in computed tomography,.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies Review of liver segmentation and computer assisted detection/diagnosis methods in computed tomography,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:45:31.594817Z

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Observation bb471e5e-fe52-458a-aaf2-f260e298dadf · outbound

This paper cites A deep learning approach to diabetes diagnosis,.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies A deep learning approach to diabetes diagnosis,

Reference 13

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Observation 83289e3a-1f15-42a3-89d8-0cc63a268595 · outbound

This paper cites Jointvit: Modeling oxygen saturation levels with joint supervision on long-tailed octa,.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies Jointvit: Modeling oxygen saturation levels with joint supervision on long-tailed octa,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-10T23:45:30.639740Z

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Observation cfeab69b-20c5-4528-82f0-7f802ac98947 · outbound

This paper cites MMCLIP: Cross-modal Attention Masked Modelling for Medical Language-Image Pre-Training.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies MMCLIP: Cross-modal Attention Masked Modelling for Medical Language-Image Pre-Training

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T23:45:30.644209Z

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Observation 589cd7dd-2716-4c5c-89fb-68849197d50f · outbound

This paper cites A landmark-based approach for instability predic- tion in distal radius fractures,.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies A landmark-based approach for instability predic- tion in distal radius fractures,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-10T23:45:30.649174Z

Source-reported events for the cited work

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Observation 60dc3e20-1564-4f9f-b332-088d95f13e85 · outbound

This paper cites Can rotational thromboelastometry rapidly identify theragnostic targets in isolated traumatic brain injury?,.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies Can rotational thromboelastometry rapidly identify theragnostic targets in isolated traumatic brain injury?,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T23:45:30.653739Z

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Observation 75a47971-61e9-41bc-81ca-1594101bd335 · outbound

This paper cites MedDet: Generative Adversarial Distillation for Efficient Cervical Disc Herniation Detection.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies MedDet: Generative Adversarial Distillation for Efficient Cervical Disc Herniation Detection

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T23:45:30.658368Z

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Observation 9d8e0b45-e81e-411c-905e-13264028b22e · outbound

This paper cites MSDet: Receptive Field Enhanced Multiscale Detection for Tiny Pulmonary Nodule.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies MSDet: Receptive Field Enhanced Multiscale Detection for Tiny Pulmonary Nodule

Reference 19

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Observation e5ef0682-c9ee-446f-b0fa-a15ef124004e · outbound

This paper cites Medical Artificial Intelligence for Early Detection of Lung Cancer: A Survey.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies Medical Artificial Intelligence for Early Detection of Lung Cancer: A Survey

Reference 20

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Observation e1f7c2d6-db60-437f-815c-7d9bcb2b299d · outbound

This paper cites Segreg: Segmenting oars by registering mr images and ct annotations,.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies Segreg: Segmenting oars by registering mr images and ct annotations,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T23:45:30.673301Z

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Observation 2d2763c2-8857-4616-b817-7a43ef743636 · outbound

This paper cites SegStitch: Multidimensional Transformer for Robust and Efficient Medical Imaging Segmentation.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies SegStitch: Multidimensional Transformer for Robust and Efficient Medical Imaging Segmentation

Reference 22

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Observation 0a46725a-1bd4-4db2-ba83-86e52a2623b3 · outbound

This paper cites Thin-thick adapter: Segmenting thin scans using thick annotations,.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies Thin-thick adapter: Segmenting thin scans using thick annotations,

Reference 23

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Observation b7b35f6a-43dc-4ff2-94cd-13d41a3231c8 · outbound

This paper cites ESA: Annotation-Efficient Active Learning for Semantic Segmentation.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies ESA: Annotation-Efficient Active Learning for Semantic Segmentation

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T23:45:30.687168Z

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Observation dc21c027-3a9c-4b79-bbba-5c9da1e3edb9 · outbound

This paper cites Robust hyperspectral image classifi- cation using a multi-scale transformer with long-short-distance spatial- spectral cross-attention,.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies Robust hyperspectral image classifi- cation using a multi-scale transformer with long-short-distance spatial- spectral cross-attention,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:45:31.516609Z

Source-reported events for the cited work

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Observation 7d821482-5239-463f-9f66-e9e8ea9a0c8a · outbound

This paper cites Csffnet: Lightweight cross-scale feature fusion network for salient object detection in remote sensing images,.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies Csffnet: Lightweight cross-scale feature fusion network for salient object detection in remote sensing images,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:45:31.498988Z

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Observation 4cabc403-0084-4ea6-af8e-88c3658ca7bd · outbound

This paper cites The gan spatiotemporal fusion model based on multi-scale convolution and attention mechanism for remote sensing images,.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies The gan spatiotemporal fusion model based on multi-scale convolution and attention mechanism for remote sensing images,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:45:31.482299Z

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Observation 6abe6cd6-3cb3-4620-a289-bd098dd33b77 · outbound

This paper cites A multi-scale cascaded cross-attention hierarchical network for change detection on bitemporal remote sensing images,.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies A multi-scale cascaded cross-attention hierarchical network for change detection on bitemporal remote sensing images,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:45:31.467567Z

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Observation b0b53680-1edd-4b8b-b9b3-dfcecae100b1 · outbound

This paper cites PGN: The RNN's New Successor is Effective for Long-Range Time Series Forecasting.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies PGN: The RNN's New Successor is Effective for Long-Range Time Series Forecasting

Reference 29

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Observation 39b22649-13c7-4076-b184-4d791fd8e2f3 · outbound

This paper cites Tltnet: A novel transscale cascade layered transformer network for enhanced retinal blood vessel segmentation,.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies Tltnet: A novel transscale cascade layered transformer network for enhanced retinal blood vessel segmentation,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:45:31.452360Z

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Observation c9a6c86b-c860-460b-acff-19a67636f20a · outbound

This paper cites Global transformer and dual local attention network via deep-shallow hierarchical feature fusion for retinal vessel segmentation,.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies Global transformer and dual local attention network via deep-shallow hierarchical feature fusion for retinal vessel segmentation,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:45:31.437851Z

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Observation 55f42063-de9b-4c3d-8b1f-df89f06035cb · outbound

This paper cites Towards large-scale small object detection: Survey and benchmarks,.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies Towards large-scale small object detection: Survey and benchmarks,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:45:31.423132Z

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Observation 3693642b-bd36-4f98-8d4e-a602b96e2bc9 · outbound

This paper cites TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis

Reference 33

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Observation 1d2ab107-9377-4164-bc5a-f95bcac7b7ac · outbound

This paper cites A Time Series is Worth 64 Words: Long-term Forecasting with Transformers.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies A Time Series is Worth 64 Words: Long-term Forecasting with Transformers

Reference 34

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Observation e7d96d25-7daa-4061-83b0-93077165c02f · outbound

This paper cites Attention is all you need,.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies Attention is all you need,

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-10T23:45:30.745887Z

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Observation cae09150-70f1-4de2-89ec-b8a48d5e2c61 · outbound

This paper cites Informer: Beyond efficient transformer for long sequence time-series forecasting,.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies Informer: Beyond efficient transformer for long sequence time-series forecasting,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:45:31.399987Z

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Observation db1e82a2-489b-4d87-9c03-f7b249519593 · outbound

This paper cites nnformer: V olumetric medical image segmentation via a 3d transformer,.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies nnformer: V olumetric medical image segmentation via a 3d transformer,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:45:31.384162Z

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Observation 5a928d4c-f09c-4b96-bc36-7253c1d1c1c9 · outbound

This paper cites Exploiting full Resolution Feature Context for Liver Tumor and Vessel Segmentation via Integrate Framework: Application to Liver Tumor and Vessel 3D Reconstruction under embedded microprocessor.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies Exploiting full Resolution Feature Context for Liver Tumor and Vessel Segmentation via Integrate Framework: Application to Liver Tumor and Vessel 3D Reconstruction under embedded microprocessor

Reference 38

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Observation 0a3e1222-8da0-441d-899f-7c23f8df7847 · outbound

This paper cites KAN: Kolmogorov-Arnold Networks.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies KAN: Kolmogorov-Arnold Networks

Reference 39

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Source-reported events for the cited work

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Observation dfa0caef-2722-4f77-83ed-5b7e8c552ef8 · outbound

This paper cites Kolmogorov-Arnold Convolutions: Design Principles and Empirical Studies.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies Kolmogorov-Arnold Convolutions: Design Principles and Empirical Studies

Reference 40

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Observation 72c92806-0ed2-4693-9950-2ecb2fca85c2 · outbound

This paper cites Fan: Fourier analysis networks,.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies Fan: Fourier analysis networks,

Reference 41

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Source-reported events for the cited work

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Observation 52e2a429-86c3-48b3-bb5f-271dfdfc8dd4 · outbound

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SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies Kolmogorov-Arnold Transformer

Reference 42

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Observation 4f2900a3-188e-42b0-8c06-1327eac47ec3 · outbound

This paper cites KAN/MultKAN with Physics-Informed Spline fitting (KAN-PISF) for ordinary/partial differential equation discovery of nonlinear dynamic systems.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies KAN/MultKAN with Physics-Informed Spline fitting (KAN-PISF) for ordinary/partial differential equation discovery of nonlinear dynamic systems

Reference 43

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Observation 88b8c0ca-8661-4b54-b103-4bb249433269 · outbound

This paper cites Wav-KAN: Wavelet Kolmogorov-Arnold Networks.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies Wav-KAN: Wavelet Kolmogorov-Arnold Networks

Reference 44

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Observation b582d6a4-effb-4c88-bcd5-09da09d25e16 · outbound

This paper cites Model Comparisons: XNet Outperforms KAN.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies Model Comparisons: XNet Outperforms KAN

Reference 45

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Observation ec0d0799-f1f5-418f-ba8a-1d59a71d9a52 · outbound

This paper cites nnu-net: a self-configuring method for deep learning-based biomedical image segmentation,.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies nnu-net: a self-configuring method for deep learning-based biomedical image segmentation,

Reference 46

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Observation e7bd1dca-1d8e-483f-9968-61052611aac4 · outbound

This paper cites Swin unetr: Swin transformers for semantic segmentation of brain tumors in mri images,.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies Swin unetr: Swin transformers for semantic segmentation of brain tumors in mri images,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:45:31.359952Z

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Observation a5591c84-5ef6-49cb-81c4-377f91707341 · outbound

This paper cites A robust volumetric transformer for accurate 3d tumor segmentation,.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies A robust volumetric transformer for accurate 3d tumor segmentation,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:45:31.345073Z

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Observation 241248b9-d0e4-4d38-8223-566b2fa46e01 · outbound

This paper cites nnFormer: Interleaved Transformer for Volumetric Segmentation.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies nnFormer: Interleaved Transformer for Volumetric Segmentation

Reference 49

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Observation e02e660f-4336-49ae-a646-d3ceb6c8f4e3 · outbound

This paper cites DeformUX-Net: Exploring a 3D Foundation Backbone for Medical Image Segmentation with Depthwise Deformable Convolution.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies DeformUX-Net: Exploring a 3D Foundation Backbone for Medical Image Segmentation with Depthwise Deformable Convolution

Reference 50

Resolution: verified exact; local_arxiv, observed 2026-08-10T23:45:30.949639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 67f9b5cc-e452-442e-be41-b79e97516933 · outbound

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

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-10T23:45:30.830098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 96fb3da7-78d9-41a0-9527-18bc89e8b58e · outbound

This paper cites Lstm: A search space odyssey,.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies Lstm: A search space odyssey,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:45:31.330459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 72f59270-1a49-488a-b7b1-ec7da36924a7 · outbound

This paper cites TimeMachine: A Time Series is Worth 4 Mambas for Long-term Forecasting.

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies TimeMachine: A Time Series is Worth 4 Mambas for Long-term Forecasting

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-10T23:45:30.840765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c70ef128-c58d-4d5b-a7f6-23f48b134ee7 · outbound

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

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-10T23:45:30.846374Z

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Unavailable: canonical work link unavailable.

Pith citing papers

Observation d9828a6b-8f9a-4f0a-960a-e3fb3d2ddfed · inbound

ProjectedEx: Enhancing Generation in Explainable AI for Prostate Cancer cites this paper.

ProjectedEx: Enhancing Generation in Explainable AI for Prostate Cancer SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T22:32:05.186019Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 177d9a66-7df2-4b75-b7ad-4690b79ee454 · inbound

GAMED-Snake: Gradient-aware Adaptive Momentum Evolution Deep Snake Model for Multi-organ Segmentation cites this paper.

GAMED-Snake: Gradient-aware Adaptive Momentum Evolution Deep Snake Model for Multi-organ Segmentation SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-10T16:46:37.045264Z

Source-reported events for the cited work

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Observation f3c5753f-0714-47fa-9c08-3035b0bb4e4a · inbound

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction cites this paper.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-09T18:19:39.292875Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 742a8a50-5134-4946-89fa-d661117123cd · inbound

A Novel Convolutional-Free Method for 3D Medical Imaging Segmentation cites this paper.

A Novel Convolutional-Free Method for 3D Medical Imaging Segmentation SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-08T19:33:21.506141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 72bdedbd-7a1b-497b-982d-207959a52b16 · inbound

SSS: Semi-Supervised SAM-2 with Efficient Prompting for Medical Imaging Segmentation cites this paper.

SSS: Semi-Supervised SAM-2 with Efficient Prompting for Medical Imaging Segmentation SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T05:03:35.609588Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 864d0c9b-9a2f-4332-81a0-5713c399b814 · inbound

SegTTA: Training-Free Test-Time Augmentation for Zero-Shot Medical Imaging Segmentation cites this paper.

SegTTA: Training-Free Test-Time Augmentation for Zero-Shot Medical Imaging Segmentation SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-10T05:41:02.379597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.