Pith. sign in

Paper Citation Record · LEDGER

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction

As of 13 August 2026, this Paper Citation Record lists 82 of 82 outbound references and 0 inbound Pith citation observations for arXiv:2411.15251.

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

pith.paper-citation-record.v1
2411.15251 v1

Coverage vector

measured 82 of 82 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T14:56:50.424986Z

measured 82 of 82 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

82 of 82 outbound references displayed

  • verified exact3
  • verified fuzzy60
  • unresolved19
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f6d06b3d-5916-4e7a-a077-72be30a5a28d · outbound

This paper cites Deep-learning based detection of vessel occlusions on CT-angiography in patients with suspected acute ischemic stroke,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Deep-learning based detection of vessel occlusions on CT-angiography in patients with suspected acute ischemic stroke,

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-12T14:56:50.088568Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:56:50.088568Z digest=sha256:e07eb31d4e3e9b24c380e550ae9a3b268b8ea5195c5a65e61d65366b73a36edf

Observation 4e1f9e4b-e083-47e1-bd37-d65030c950db · outbound

This paper cites Annotation-efficient deep learning for automatic medical image segmentation,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Annotation-efficient deep learning for automatic medical image segmentation,

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-12T14:56:50.093124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:56:50.093124Z digest=sha256:3113274338f698983c09b07d468699f4b8cee88d1c7c0947a7985c3c3c464a25

Observation 45d2b7a2-fb0a-47f9-b393-238b5e653ecc · outbound

This paper cites Detection of blood vessels in retinal images using two-dimensional matched filters,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Detection of blood vessels in retinal images using two-dimensional matched filters,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:51.407032Z

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.

source=pdf_text observed=2026-08-12T14:56:50.097230Z digest=sha256:61f6baad799064c6fd67b3d07c70d43d9467050078c4a2d36838d1e27234fe40

Observation c1c1cab8-ddca-45ae-ae47-045682281ad4 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Swin transformer: Hierarchical vision transformer using shifted windows,

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-12T14:56:50.105378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:56:50.105378Z digest=sha256:d41d92b1edd56b95e383ceace6362fdd3b75dafefc3d2679ed7e34d3e42fa757

Observation 38c70e97-ae07-4b2d-b40f-24e57ec15185 · outbound

This paper cites ImageNet Classifica- tion with Deep Convolutional Neural Networks,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction ImageNet Classifica- tion with Deep Convolutional Neural Networks,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:51.370485Z

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.

source=pdf_text observed=2026-08-12T14:56:50.110255Z digest=sha256:1b1f327b3aef5aa640fd9acffc130d5ede59bcb68b62101a0c1e3574111af497

Observation 1552e362-efba-4e43-b0c4-a9f2e69a6d66 · outbound

This paper cites Large-scale Multi-modal Pre-trained Models: A Comprehen- sive Survey,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Large-scale Multi-modal Pre-trained Models: A Comprehen- sive Survey,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:51.357481Z

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.

source=pdf_text observed=2026-08-12T14:56:50.114094Z digest=sha256:2f455a2585b2e12f451949f30002083bc9bd8e98132f578b497684bf01940d6d

Observation b6a8fb00-9c2e-4990-a236-65d8654debe4 · outbound

This paper cites Segment Anything,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Segment Anything,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:51.345211Z

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.

source=pdf_text observed=2026-08-12T14:56:50.117438Z digest=sha256:8c8f43ea260aeb82bfa4082aad2b75b7de5f790c450d6affd76f7a12cc4456cd

Observation 3f8324bd-78a1-419a-93a8-ccda218b2c77 · outbound

This paper cites Segment Anything Model for Medical Images?.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Segment Anything Model for Medical Images?

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:51.333151Z

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.

source=pdf_text observed=2026-08-12T14:56:50.120929Z digest=sha256:262a1a0fbaf4bd8b0344f54047f3b5cf401556b05c30100ade6ca42432268b11

Observation bf7d367a-b052-4b0d-9cbe-369c78a0a5c1 · outbound

This paper cites Synergistic image and feature adaptation: Towards cross-modality domain adaptation for medical image segmentation,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Synergistic image and feature adaptation: Towards cross-modality domain adaptation for medical image segmentation,

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-12T14:56:50.124458Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:56:50.124458Z digest=sha256:8b12a60c8b65d88f53c5744b67065a53d2817c05f4f214d84172125395317980

Observation d22a899c-a31b-456b-8663-24409d52210e · outbound

This paper cites A Deep Learning Design for Improving Topology Coherence in Blood Vessel Segmentation,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction A Deep Learning Design for Improving Topology Coherence in Blood Vessel Segmentation,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:51.315390Z

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.

source=pdf_text observed=2026-08-12T14:56:50.128485Z digest=sha256:5ea88deecfb39949b349ea61a6322d89f60be2a33bb656d3808fa9be7ad7fe8d

Observation d01fba45-c48c-442c-a256-90df91c22e95 · outbound

This paper cites clDice – A Novel Topology- Preserving Loss Function for Tubular Structure Segmentation,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction clDice – A Novel Topology- Preserving Loss Function for Tubular Structure Segmentation,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:51.302782Z

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.

source=pdf_text observed=2026-08-12T14:56:50.131938Z digest=sha256:ae046733ab19348b125f53794c6d7e0c0451e52b74f1fc5a63b7edbafc15004a

Observation c7e81a57-8ee5-4df9-8df3-e13b56dfd798 · outbound

This paper cites SCS-Net: A Scale and Context Sensitive Network for Retinal Vessel Segmentation,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction SCS-Net: A Scale and Context Sensitive Network for Retinal Vessel Segmentation,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:51.288982Z

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.

source=pdf_text observed=2026-08-12T14:56:50.135888Z digest=sha256:5e0127258751d0b8b9e38a8c9c5e777788f7339e9a8f8ec68373aa8a68245a08

Observation de4c028c-020b-43ef-972a-2dc862ea5947 · outbound

This paper cites Covi-net: A hybrid convolutional and vision transformer neural network for retinal vessel segmentation,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Covi-net: A hybrid convolutional and vision transformer neural network for retinal vessel segmentation,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:51.276846Z

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.

source=pdf_text observed=2026-08-12T14:56:50.139463Z digest=sha256:e100f0c57ed98600b0e0b3fc78667c7bca6f0a0b9dcc6eadaac6ff6b5b78a32b

Observation 512b368a-fc32-4739-8b09-1fa3e6aba758 · outbound

This paper cites Cross-patch feature interactive net with edge refinement for retinal vessel segmentation,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Cross-patch feature interactive net with edge refinement for retinal vessel segmentation,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:51.264689Z

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.

source=pdf_text observed=2026-08-12T14:56:50.143131Z digest=sha256:f18f8d8a473edf8cf7a714722b13168136b935953cd23374e775138954443ff2

Observation 34252b4d-30e8-405b-9137-a104974ce35c · outbound

This paper cites Retinal OCTA Image Segmen- tation Based on Global Contrastive Learning,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Retinal OCTA Image Segmen- tation Based on Global Contrastive Learning,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:51.240944Z

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.

source=pdf_text observed=2026-08-12T14:56:50.151106Z digest=sha256:df330b56429b3fc31fa71740352b2e2d20e752d6c9c19a4f0eba17730667986b

Observation c2bfbd71-dc18-46be-b5a7-a4747f2f3d1e · outbound

This paper cites Rose: A Retinal OCT-Angiography Vessel Segmentation Dataset and New Model,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Rose: A Retinal OCT-Angiography Vessel Segmentation Dataset and New Model,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:51.227344Z

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.

source=pdf_text observed=2026-08-12T14:56:50.154728Z digest=sha256:f5d458c6e1e6a097e76e09dfa6306609366b34a064f1ff13de29ebbf572e4754

Observation 04650740-8aa1-4683-82e3-bfc104fb5c88 · outbound

This paper cites Optimizing ensemble U-Net architectures for robust coronary vessel segmentation in angiographic images,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Optimizing ensemble U-Net architectures for robust coronary vessel segmentation in angiographic images,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:51.216006Z

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.

source=pdf_text observed=2026-08-12T14:56:50.158684Z digest=sha256:0d87797427877bf3070e50c6e6794f2008ca7111ae76084589456c1eb9db088f

Observation 7092af25-271f-4ad3-9b05-0f6dce6fb74e · outbound

This paper cites Segment anything in medical images,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Segment anything in medical images,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:51.192584Z

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.

source=pdf_text observed=2026-08-12T14:56:50.171053Z digest=sha256:19f4453792a1f860c20fdfc78eccaec12e78a1f4ab20ad049262e7609ebd265c

Observation 2d78fada-64f3-4606-9208-3c7334308615 · outbound

This paper cites SAM-Med2D.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction SAM-Med2D

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-12T14:56:50.175012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:56:50.175012Z digest=sha256:d643e42c65c46610f05929fb723d8f653277699be5bbba5f5c84eb74c8bd34b7

Observation e22aadbe-4468-4213-b15d-2a4802652bdb · outbound

This paper cites Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-12T14:56:50.179865Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:56:50.179865Z digest=sha256:bcd3f71669d7d24d6611e111b11affb4d993678e31c9eed9440802c1d63d7d34

Observation 416ed04e-1db4-4f66-8628-9bfd59822989 · outbound

This paper cites Customized Segment Anything Model for Medical Image Segmentation.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Customized Segment Anything Model for Medical Image Segmentation

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-12T14:56:50.183970Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:56:50.183970Z digest=sha256:a062b0a8fe52abadcbe422e2085037f81d85b80d2f89613adb3bd5a02a02f7b7

Observation 8fae4ab4-c508-4816-ae35-14d0dc09835f · outbound

This paper cites Ladder Fine-tuning approach for SAM integrating complementary network.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Ladder Fine-tuning approach for SAM integrating complementary network

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-12T14:56:50.188109Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:56:50.188109Z digest=sha256:68896865a9d5ce4eade211bd23015e6fc3a3fb65d0a0c30b1ae23254e1d216fc

Observation 56bfdc56-98a5-4439-8efc-c55014fde3f9 · outbound

This paper cites Beyond Adapting SAM: Towards End-to-End Ultrasound Image Segmentation via Auto Prompting.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Beyond Adapting SAM: Towards End-to-End Ultrasound Image Segmentation via Auto Prompting

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-12T14:56:50.191963Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:56:50.191963Z digest=sha256:9850437e894728baee8d107f71cceed323515a0a4b0c107c573ed630f0181211

Observation 71e69263-e661-4e8b-b463-a2bf55696225 · outbound

This paper cites DB-SAM: Delving into High Quality Universal Medical Image Segmentation.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction DB-SAM: Delving into High Quality Universal Medical Image Segmentation

Reference 27

Resolution
verified exact
local_arxiv, observed 2026-08-12T14:56:50.565867Z

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.

source=pdf_text observed=2026-08-12T14:56:50.196000Z digest=sha256:22cae79971d30befb35d0be1aed3383f22a7ce5ff6d59c244d20ae70518dc894

Observation 4a298134-43cc-4cd7-b943-feff122421d9 · outbound

This paper cites Segment Anything in High Quality,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Segment Anything in High Quality,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:51.177348Z

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.

source=pdf_text observed=2026-08-12T14:56:50.199730Z digest=sha256:52a9e6cca4fc17dcf00706e4055dec96e3815c6b07eed9f74ca60ca2fbc6fa7d

Observation 2529c406-be70-4c5e-9056-e0d102c45f61 · outbound

This paper cites Mamba or RWKV: Exploring High-Quality and High-Efficiency Segment Anything Model.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Mamba or RWKV: Exploring High-Quality and High-Efficiency Segment Anything Model

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-12T14:56:50.203340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:56:50.203340Z digest=sha256:f73a2c566c39b1f977b85397359fa672eca97a88f907029e34ac96c197e2bcff

Observation 93081182-c602-4a02-aeb7-a5ee91c4eaf1 · outbound

This paper cites CorSegRec: A Topology-Preserving Scheme for Extracting Fully-Connected Coronary Arteries from CT Angiography,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction CorSegRec: A Topology-Preserving Scheme for Extracting Fully-Connected Coronary Arteries from CT Angiography,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:51.165806Z

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.

source=pdf_text observed=2026-08-12T14:56:50.207415Z digest=sha256:173a7dbb4fc1c9dab9523cfa3a44b1fb2e00256f10323b58bf22709e362b079f

Observation 95cc80ca-97f8-42a5-a067-2bb9b0cff295 · outbound

This paper cites Deep Closing: Enhancing Topological Connectivity in Medical Tubular Segmentation,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Deep Closing: Enhancing Topological Connectivity in Medical Tubular Segmentation,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:51.154618Z

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.

source=pdf_text observed=2026-08-12T14:56:50.211108Z digest=sha256:4ef19910e9579ed14fa09502703030e8bdc51612aa6cb5e1fbb68e0294aa8ce3

Observation b4eacf96-4cba-4e01-a9fe-68c73f8c06fa · outbound

This paper cites Convolutional CRFs for Semantic Segmentation.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Convolutional CRFs for Semantic Segmentation

Reference 32

Resolution
verified exact
local_arxiv, observed 2026-08-12T14:56:50.539267Z

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.

source=pdf_text observed=2026-08-12T14:56:50.214869Z digest=sha256:075c37f4766b150c676b22dfc8c6f31e23059c42ed3d21a28c7597ef5ff43404

Observation 3e5070fd-9ca3-48f3-88a1-af78ebab4997 · outbound

This paper cites DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentation,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentation,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:51.143135Z

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.

source=pdf_text observed=2026-08-12T14:56:50.218831Z digest=sha256:c8878155ce458ecd8fa83bb12b91a5a01b6d22662877c6c293dc89f26c34b212

Observation f571dc8e-a3cc-4c44-8e07-6341df9c05ae · outbound

This paper cites VSR-Net: Vessel-like Structure Rehabilitation Network with Graph Clustering.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction VSR-Net: Vessel-like Structure Rehabilitation Network with Graph Clustering

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-12T14:56:50.222583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:56:50.222583Z digest=sha256:5dc2a4da47ddff40518dac5fec45e24e0404bb0d4820eb2faba5924e7e891f81

Observation 7940780c-d9a0-4d93-8aea-b39a4dd5b3ae · outbound

This paper cites SegRefiner: Towards Model-Agnostic Segmentation Refinement with Discrete Dif- fusion Process,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction SegRefiner: Towards Model-Agnostic Segmentation Refinement with Discrete Dif- fusion Process,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:51.131034Z

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.

source=pdf_text observed=2026-08-12T14:56:50.226712Z digest=sha256:a2f139e56e67b3ebaff8719b863b3f7838640ac0139e3103a74255b3f907454f

Observation 51b053f4-8efa-490d-a6b8-b86c8f391daa · outbound

This paper cites Masked Autoencoders Are Scalable Vision Learners,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Masked Autoencoders Are Scalable Vision Learners,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:51.119085Z

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.

source=pdf_text observed=2026-08-12T14:56:50.230464Z digest=sha256:60af22ec378bd95aec579dc2e254077a33d2ae2dfc00a473c428f38370f718ef

Observation 8e7d3b99-95ee-4f55-bf01-b3c79b0f0e99 · outbound

This paper cites A ConvNet for the 2020s,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction A ConvNet for the 2020s,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:51.107562Z

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.

source=pdf_text observed=2026-08-12T14:56:50.234730Z digest=sha256:a0fdf5f554b4bdb9b4316742d0db93bcc663936160a16a6ff66887e3f910c4f2

Observation 2090d13a-96ea-41af-9260-dd104e2004d3 · outbound

This paper cites Automatic Segmentation of Coronary Arteries in X-ray Angiograms using Multiscale Analysis and Artificial Neural Networks,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Automatic Segmentation of Coronary Arteries in X-ray Angiograms using Multiscale Analysis and Artificial Neural Networks,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:51.096061Z

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.

source=pdf_text observed=2026-08-12T14:56:50.238772Z digest=sha256:e1106405ee926054715e176ddcc1a8e8a686f293def752780efd47d4848f0d2a

Observation 2b1caa5e-3872-4cd9-929f-8ada5c7ae0ca · outbound

This paper cites Self-Supervised Vessel Segmentation via Adversarial Learning,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Self-Supervised Vessel Segmentation via Adversarial Learning,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:51.084744Z

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.

source=pdf_text observed=2026-08-12T14:56:50.242432Z digest=sha256:aa37149e73a93ffb6831772d240e13cb5d460201b752cc703e7b673a0b39c83c

Observation 20d15bec-1fa2-48ed-99f9-803018a88e98 · outbound

This paper cites Enhancement of blood vessels in digital fundus photographs via the application of multiscale line operators,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Enhancement of blood vessels in digital fundus photographs via the application of multiscale line operators,

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-12T14:56:50.246196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:56:50.246196Z digest=sha256:cf0855744408b57db316106735ff5336fe6d67c1279cf5bdc1277049075c5ec9

Observation 6e622209-de10-45eb-9da5-9db9d4ff9e10 · outbound

This paper cites Measuring retinal vessel tortu- osity in 10-year-old children: validation of the Computer-Assisted Image Analysis of the Retina (CAIAR) program,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Measuring retinal vessel tortu- osity in 10-year-old children: validation of the Computer-Assisted Image Analysis of the Retina (CAIAR) program,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:51.066889Z

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.

source=pdf_text observed=2026-08-12T14:56:50.249932Z digest=sha256:8566c9de29f9194a03da0aa9d98b2960515db0c5959f3a7d8e556f6abaae0924

Observation 7d181fdc-f88d-48f5-8a96-a532e2b90fa0 · outbound

This paper cites DR HAGIS- a fundus image database for the automatic extraction of retinal surface vessels from diabetic patients,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction DR HAGIS- a fundus image database for the automatic extraction of retinal surface vessels from diabetic patients,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:51.054646Z

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.

source=pdf_text observed=2026-08-12T14:56:50.253911Z digest=sha256:3674c0f23029df59de203267e0dd2128784e47464bc50d750dab433b949a1ef7

Observation bee92fd8-c1f8-4211-801d-023cdba4ef53 · outbound

This paper cites Ridge-based vessel segmentation in color images of the retina,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Ridge-based vessel segmentation in color images of the retina,

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-12T14:56:50.257614Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:56:50.257614Z digest=sha256:8cd49561afd9c5492bfd710cf5e0c96bf7a8c906db3a776782118223caf5acf5

Observation bf4e46cd-88ac-4c86-b55e-20d87a125a15 · outbound

This paper cites FIVES: A Fundus Image Dataset for Artificial Intelligence based Vessel Segmentation,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction FIVES: A Fundus Image Dataset for Artificial Intelligence based Vessel Segmentation,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:51.035429Z

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.

source=pdf_text observed=2026-08-12T14:56:50.261497Z digest=sha256:5d9cd7bf2dfb2e6c483df026e15616c500aa7e92d2381a8c86fa1c0e1a4d54c6

Observation 2694172e-cd6d-4cac-8751-5389dc87be2f · outbound

This paper cites Retinal vessel segmentation by improved matched filtering: evaluation on a new high-resolution fundus image database,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Retinal vessel segmentation by improved matched filtering: evaluation on a new high-resolution fundus image database,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:51.023870Z

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.

source=pdf_text observed=2026-08-12T14:56:50.265417Z digest=sha256:219d702b97910f0a7cf26731236dd37f5cf090d2915bfb21b40e7914ede54af2

Observation 8b56804c-be0e-4aba-bb42-32daaf36dda8 · outbound

This paper cites Robust Retinal Vessel Segmentation via Locally Adaptive Derivative Frames in Orientation Scores,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Robust Retinal Vessel Segmentation via Locally Adaptive Derivative Frames in Orientation Scores,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:51.009991Z

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.

source=pdf_text observed=2026-08-12T14:56:50.269514Z digest=sha256:7ae16c87a9f27c4513985ca2fce359a7ccf25f4fc405f47490872d6f0529fff1

Observation ef9b43c3-6c2f-40e0-b2cb-31e7dcaf4106 · outbound

This paper cites Towards a glaucoma risk index based on simulated hemodynamics from fundus images,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Towards a glaucoma risk index based on simulated hemodynamics from fundus images,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:50.997259Z

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.

source=pdf_text observed=2026-08-12T14:56:50.273929Z digest=sha256:5d06b178890c7ffb064c9d6888cf221b9445dfbb85668133cb0d1709adb8a5cb

Observation 9c298e0f-1732-4321-9791-efcacb606d5d · outbound

This paper cites Transfer Learning Through Weighted Loss Function and Group Normalization for Vessel Segmentation from Retinal Images,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Transfer Learning Through Weighted Loss Function and Group Normalization for Vessel Segmentation from Retinal Images,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:50.984275Z

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.

source=pdf_text observed=2026-08-12T14:56:50.277974Z digest=sha256:b6cd64d1d30dafdc5893a9bbb9809e127e047add2d9de9679a3848876684ed29

Observation 037ca9f5-93f7-44b1-9994-556e3c6e4548 · outbound

This paper cites Locating blood vessels in retinal images by piecewise threshold probing of a matched filter response,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Locating blood vessels in retinal images by piecewise threshold probing of a matched filter response,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:51.392938Z

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.

source=pdf_text observed=2026-08-12T14:56:50.281827Z digest=sha256:cddd38f40ef09dcb364969bee781f30e03886409dd29f52c5ccb91520e8ba875

Observation 24cdaf6c-19ec-46cc-85db-c98fce28c2d3 · outbound

This paper cites An Accurate and Efficient Neural Network for OCTA Vessel Segmentation and a New Dataset,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction An Accurate and Efficient Neural Network for OCTA Vessel Segmentation and a New Dataset,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:51.253118Z

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.

source=pdf_text observed=2026-08-12T14:56:50.285536Z digest=sha256:ced720179c5cdf8af61f325a19fc0f237e504f139b6982e11b32b98dc21ee2e1

Observation 1194b56f-d4b5-498f-93c6-efd72995dfe6 · outbound

This paper cites OCTA-500: A Retinal Dataset for Optical Coherence Tomography Angiography Study,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction OCTA-500: A Retinal Dataset for Optical Coherence Tomography Angiography Study,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:50.970503Z

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.

source=pdf_text observed=2026-08-12T14:56:50.288965Z digest=sha256:04729e959cb672bec7e5491674f70bcdf45116f29aca8433564a4ecbd216054f

Observation 4b1210c5-7f74-4c04-b228-b8293a94c502 · outbound

This paper cites Dr-SAM: An End-to-End Framework for Vascular Segmentation Diameter Estimation and Anomaly Detection on An- giography Images,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Dr-SAM: An End-to-End Framework for Vascular Segmentation Diameter Estimation and Anomaly Detection on An- giography Images,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:50.955832Z

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.

source=pdf_text observed=2026-08-12T14:56:50.294994Z digest=sha256:29df9200cfbb6c45957df9fc9744145fd8c051099291d69ed3d2987d57c70c1a

Observation 01ec9f4e-2091-4931-88b2-f6bf04f776fd · outbound

This paper cites How to build the best medical image segmentation algorithm using foundation models: a comprehensive empirical study with Segment Anything Model.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction How to build the best medical image segmentation algorithm using foundation models: a comprehensive empirical study with Segment Anything Model

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-12T14:56:50.298999Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:56:50.298999Z digest=sha256:42964d643f125309c2f8fb4ddac821642353eb0757ed1b43cd983985bf0af419

Observation db55ba98-cde5-4f8b-9b5a-0796bdaeb288 · outbound

This paper cites Improved Baselines with Synchronized Encoding for Universal Medical Image Segmentation.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Improved Baselines with Synchronized Encoding for Universal Medical Image Segmentation

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-12T14:56:50.302957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:56:50.302957Z digest=sha256:2daa9dedabd38876cf2b8c481a334cb03d78a5f9a03a584a4c93a5701da68533

Observation 822ad230-5d43-41cf-80c5-6481b24b7eaa · outbound

This paper cites SPIRONet: Spatial-Frequency Learning and Graph-based Channel Interaction Network for Vessel Segmentation.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction SPIRONet: Spatial-Frequency Learning and Graph-based Channel Interaction Network for Vessel Segmentation

Reference 55

Resolution
verified exact
local_arxiv, observed 2026-08-12T14:56:50.489290Z

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.

source=pdf_text observed=2026-08-12T14:56:50.307506Z digest=sha256:ea51c3cc767f9a55cf1e91597503fefdc977009dabafceefa5f062ed46968684

Observation e090094f-673f-4cf3-ac5b-c2f92e3fd524 · outbound

This paper cites Full-Resolution Network and Dual-Threshold Iteration for Retinal Vessel and Coronary Angiograph Segmentation,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Full-Resolution Network and Dual-Threshold Iteration for Retinal Vessel and Coronary Angiograph Segmentation,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:51.204028Z

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.

source=pdf_text observed=2026-08-12T14:56:50.311432Z digest=sha256:9fd281934bdca4a2d1c256de090638604096682bfb8760a496c9b95a895177be

Observation b7b95cfa-da9b-4015-b285-77d2bff09140 · outbound

This paper cites OCT2Former: A retinal OCT-angiography vessel segmentation transformer,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction OCT2Former: A retinal OCT-angiography vessel segmentation transformer,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:50.944416Z

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.

source=pdf_text observed=2026-08-12T14:56:50.314904Z digest=sha256:cb85f2594fb023bf7426fc9c3463decb1ce2ebd9773d95e6f32eee6723d81de2

Observation c8d18de0-b001-4ed7-8917-d866f1ee6dd3 · outbound

This paper cites Feature Enhancer Segmentation Network (FES-Net) for Vessel Segmentation,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Feature Enhancer Segmentation Network (FES-Net) for Vessel Segmentation,

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:50.932907Z

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.

source=pdf_text observed=2026-08-12T14:56:50.318569Z digest=sha256:8a84bde4331b5676b27e8cc96cb318d92f0fc196749cdfd89927c1aad64aa865

Observation 5725775b-a258-4a0d-8ffd-5aaebe4f4576 · outbound

This paper cites LMBiS-Net: A lightweight bidirectional skip connection based multipath CNN for retinal blood vessel segmentation,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction LMBiS-Net: A lightweight bidirectional skip connection based multipath CNN for retinal blood vessel segmentation,

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:50.920521Z

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.

source=pdf_text observed=2026-08-12T14:56:50.322057Z digest=sha256:9cbd846f5f591606cf342736ce9ce0c7dad41fd1028093f0888780afabca321a

Observation 4117cbaa-a1d3-4d8f-8469-6f9fb712cd7f · outbound

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

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction U-net: Convolutional networks for biomedical image segmentation,

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-12T14:56:50.325723Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:56:50.325723Z digest=sha256:1c908ab997195ff79c20a42d1721194d702aabc1e582279bca8685704575cef6

Observation 5b13ad42-03d0-41be-9857-f15845ae3264 · outbound

This paper cites UNet++: A Nested U-Net Architecture for Medical Image Segmen- tation,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction UNet++: A Nested U-Net Architecture for Medical Image Segmen- tation,

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:50.900064Z

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.

source=pdf_text observed=2026-08-12T14:56:50.329389Z digest=sha256:f2d82efff2954c2de6b34efbf7c884d6f3c0f5ece3d5b8ea732bf29bde6d8b7d

Observation 074e8ace-e74a-4001-91c7-a904a27fd244 · outbound

This paper cites Attention U- Net: Learning Where to Look for the Pancreas,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Attention U- Net: Learning Where to Look for the Pancreas,

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:50.888028Z

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.

source=pdf_text observed=2026-08-12T14:56:50.332860Z digest=sha256:4d63d1ba99255f25a0d45369e1b9ce76193437f04078d6ce7e1d2d98047e71e2

Observation 1701a2d8-93f2-4a42-988c-f859e02c6835 · outbound

This paper cites CE-Net: Context Encoder Network for 2D Medical Image Segmentation,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction CE-Net: Context Encoder Network for 2D Medical Image Segmentation,

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:50.875237Z

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.

source=pdf_text observed=2026-08-12T14:56:50.337589Z digest=sha256:862a0b12a724e6377557142eb0e29c47996b59cfca313f21e49bb6bb729effd1

Observation 8a4a3a2a-d51f-43a0-9cfd-9f40345ed829 · outbound

This paper cites CAU-net: A Novel Convolutional Neural Network for Coronary Artery Segmentation in Digital Substraction angiography,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction CAU-net: A Novel Convolutional Neural Network for Coronary Artery Segmentation in Digital Substraction angiography,

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:50.861998Z

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.

source=pdf_text observed=2026-08-12T14:56:50.342024Z digest=sha256:8ab12e8a1ce636a96a03ea8e1da9791133c2769863af4278a2694c1178424191

Observation 7629b5c6-9fa7-4e75-a9eb-da02d02f1265 · outbound

This paper cites CS2-Net: Deep Learning Segmentation of Curvilinear Structures in Medical Imaging,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction CS2-Net: Deep Learning Segmentation of Curvilinear Structures in Medical Imaging,

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:50.848952Z

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.

source=pdf_text observed=2026-08-12T14:56:50.345459Z digest=sha256:9bc61a60c89668091ec761c6a0607327326c50f3d7170b39494f38702ff78711

Observation 6d909d86-cbf5-472b-b49c-4f64024cbe1a · outbound

This paper cites Dual Encoder-Based Dynamic-Channel Graph Convolutional Network With Edge Enhancement for Retinal Vessel Segmentation,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Dual Encoder-Based Dynamic-Channel Graph Convolutional Network With Edge Enhancement for Retinal Vessel Segmentation,

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:50.837290Z

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.

source=pdf_text observed=2026-08-12T14:56:50.349018Z digest=sha256:ab9cc2b88eb422a891596c0bcb6ad98175a1d2c554fc41da6b068b203fd31cc6

Observation 4e764f64-dd0e-44a8-a4dd-daf62fcb6c89 · outbound

This paper cites Global Transformer and Dual Local Attention Network via Deep-Shallow Hierarchical Feature Fusion for Retinal Vessel Segmentation,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Global Transformer and Dual Local Attention Network via Deep-Shallow Hierarchical Feature Fusion for Retinal Vessel Segmentation,

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:50.826126Z

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.

source=pdf_text observed=2026-08-12T14:56:50.353038Z digest=sha256:aa96728f1379e2a6f9713f68a8d45a5efca9de768a485a54dff31844f15a41fb

Observation 81caa5fb-b6c5-4c5f-9fc4-fde3d20bd7ae · outbound

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

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-12T14:56:50.356913Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:56:50.356913Z digest=sha256:6223d6c34eba41a2c8f0cebb8540eb05d06e4164e80a03b6139711aa59ba15b9

Observation edb41133-8771-438a-9e4e-3aad1e564634 · outbound

This paper cites CS-Net: Channel and Spatial Attention Network for Curvilinear Structure Segmentation,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction CS-Net: Channel and Spatial Attention Network for Curvilinear Structure Segmentation,

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:50.814905Z

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.

source=pdf_text observed=2026-08-12T14:56:50.361144Z digest=sha256:3b201f38832cc9df6d0b04d3b4e479ae2910d01fb8ba2a61925c44421e1346c6

Observation 4e419381-c1f6-4622-9957-f43db9fdb92e · outbound

This paper cites H2Former: An Efficient Hierarchical Hybrid Transformer for Medical Image Segmen- tation,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction H2Former: An Efficient Hierarchical Hybrid Transformer for Medical Image Segmen- tation,

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-12T14:56:50.364949Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:56:50.364949Z digest=sha256:788c9a8c764139ee5b6d6d39b96c6e1c2f4adfe09a1737e2d81b24a705fb9b2c

Observation dd10ee19-d839-4b47-85fe-1456782eac40 · outbound

This paper cites MFI-Net: Multiscale Feature Interaction Network for Retinal Vessel Segmentation,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction MFI-Net: Multiscale Feature Interaction Network for Retinal Vessel Segmentation,

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:50.795155Z

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.

source=pdf_text observed=2026-08-12T14:56:50.369077Z digest=sha256:9c5e86c2356ed793abbbc37229013fc00b3ce047795e94080f1b1cc5f62a70b6

Observation 2b627161-236d-4a9b-8115-f67e1465cd16 · outbound

This paper cites Swin-Unet: Unet-like Pure Transformer for Medical Image Segmenta- tion,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Swin-Unet: Unet-like Pure Transformer for Medical Image Segmenta- tion,

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:50.784091Z

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.

source=pdf_text observed=2026-08-12T14:56:50.373215Z digest=sha256:774ac1e8e4a25108b678a205c3efec8256651540deb9b5f388d86a8c7cfcfd7c

Observation 764671b6-a801-4551-94ab-f71918ae99be · outbound

This paper cites A Deep Neural Network for Vessel Segmentation of Scanning Laser Ophthalmoscopy Images,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction A Deep Neural Network for Vessel Segmentation of Scanning Laser Ophthalmoscopy Images,

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:50.772129Z

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.

source=pdf_text observed=2026-08-12T14:56:50.377052Z digest=sha256:8ef73044b033b657ccf56bbd2c400cd568a89f9a38edf6eba05fae4eb044ee82

Observation 5061f21a-e9c6-47d4-9945-dceb7844912b · outbound

This paper cites SA- UNet: Spatial Attention U-Net for Retinal Vessel Segmentation,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction SA- UNet: Spatial Attention U-Net for Retinal Vessel Segmentation,

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:50.760010Z

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.

source=pdf_text observed=2026-08-12T14:56:50.380734Z digest=sha256:26c066087ce3eb935faa010a0183bdb459aac998d2ee2ed7a1e44aadd63e0d73

Observation c50a2a67-93fe-4ef3-98d9-306eb92a097d · outbound

This paper cites Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation

Reference 75

Resolution
unresolved
no resolver link, observed 2026-08-12T14:56:50.384602Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:56:50.384602Z digest=sha256:f8b85d7e013ca2cf513446bd7cb8963141d215f741891f7b05f1985338232dd9

Observation 45658425-a22e-49a4-a14a-08a59e7d6243 · outbound

This paper cites Automatic 2-D/3-D Vessel Enhancement in Multiple Modality Images Using a Weighted Symmetry Filter,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Automatic 2-D/3-D Vessel Enhancement in Multiple Modality Images Using a Weighted Symmetry Filter,

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:50.747947Z

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.

source=pdf_text observed=2026-08-12T14:56:50.389222Z digest=sha256:935cf6179c193e5634237d69136eb31646f30f9c0b22df52f519337d04d0ad32

Observation 038553da-6810-477b-be4c-480c749e32f7 · outbound

This paper cites Collaborative Network for Super- Resolution and Semantic Segmentation of Remote Sensing Images,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Collaborative Network for Super- Resolution and Semantic Segmentation of Remote Sensing Images,

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:50.736915Z

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.

source=pdf_text observed=2026-08-12T14:56:50.393966Z digest=sha256:48601fe54fe88ca44f59b9acc2e07104924b0cc59fcb3f68c4588d1509997378

Observation 8b9b7027-5eb6-4f6a-b38a-9dccaa332229 · outbound

This paper cites A visual attention guided unsupervised feature learning for robust vessel delineation in retinal images,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction A visual attention guided unsupervised feature learning for robust vessel delineation in retinal images,

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:50.725544Z

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.

source=pdf_text observed=2026-08-12T14:56:50.398756Z digest=sha256:11a0b083afa4198be2b918f7995e512a0ce66efed1f4ac445acb3d6dc28dc184

Observation b5309d34-e315-4a00-b1f7-5798b0fe41d5 · outbound

This paper cites SuperVessel: Seg- menting High-Resolution Vessel from Low-Resolution Retinal Image,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction SuperVessel: Seg- menting High-Resolution Vessel from Low-Resolution Retinal Image,

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:50.714365Z

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.

source=pdf_text observed=2026-08-12T14:56:50.402637Z digest=sha256:4ae5d4dacb6751a8bfb6df489392a2d8921b354405bc826760a32b400777de57

Observation e4319147-2f93-4b09-b335-dd2b383b1b9c · outbound

This paper cites Retinal Vessel Segmentation Using Multi-Scale Residual Convolutional Neural Network (MSR-Net) Combined with Generative Adversarial Networks,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Retinal Vessel Segmentation Using Multi-Scale Residual Convolutional Neural Network (MSR-Net) Combined with Generative Adversarial Networks,

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:50.701524Z

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.

source=pdf_text observed=2026-08-12T14:56:50.406325Z digest=sha256:7f9d22125d726ab74dcfacb7b04f8521213f24eef789e1394ec310cb280ba01a

Observation 4e580d12-91d5-4ba5-9d66-45c5a1d01258 · outbound

This paper cites SUD-GAN: Deep Convolution Generative Adversarial Network Combined with Short Connection and Dense Block for Retinal Vessel Segmentation,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction SUD-GAN: Deep Convolution Generative Adversarial Network Combined with Short Connection and Dense Block for Retinal Vessel Segmentation,

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:50.688923Z

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.

source=pdf_text observed=2026-08-12T14:56:50.409887Z digest=sha256:fd3649f486b0f2293684a8e2b2cb59da2f5f229cf15ac215faeda8e0af9a1385

Observation 4c52b170-7df6-49bd-8ff2-abe47467e900 · outbound

This paper cites ErrorNet: Learning er- ror representations from limited data to improve vascular segmentation,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction ErrorNet: Learning er- ror representations from limited data to improve vascular segmentation,

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:50.677140Z

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.

source=pdf_text observed=2026-08-12T14:56:50.413684Z digest=sha256:c2287b87c36898ee685bf63f4539f5dab231d30b7918a93bdb29156ef65e3f88

Observation 2e78a40f-3340-4c65-86a3-92057031780d · outbound

This paper cites Topology-Preserving Deep Im- age Segmentation,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Topology-Preserving Deep Im- age Segmentation,

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:50.663764Z

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.

source=pdf_text observed=2026-08-12T14:56:50.417360Z digest=sha256:970bac150771800fa10e0dbb7fe4c1b840eb9da38720c98741d6537d7e8fa1b1

Observation 82673983-9823-4184-872c-79696d8e60d6 · outbound

This paper cites Local Intensity Order Transformation for Robust Curvilinear Object Segmentation,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Local Intensity Order Transformation for Robust Curvilinear Object Segmentation,

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:50.650450Z

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.

source=pdf_text observed=2026-08-12T14:56:50.421001Z digest=sha256:5b3073ee6dfe184e96275308e47630ce52eec1286138e760727f46bcc73fe83a

Observation 5399392a-ff21-4b70-b01b-2b878c04ff94 · outbound

This paper cites Directional Connectivity-based Segmentation of Medical Images,.

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction Directional Connectivity-based Segmentation of Medical Images,

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:56:50.637908Z

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.

source=pdf_text observed=2026-08-12T14:56:50.424986Z digest=sha256:37c66518d086eb08a31f3aabf19c6a55124b30e509b1ee5840bae93b48dc3069

Pith citing papers

No inbound Pith citation observations are available.