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 2026-08-13T06:32:02.005865+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=sha256:40bee2572df904993102a1396d3d1943c225ae92d0910d8942df06887253165a

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:a4412dd8d9b9ce54484ba46072e3201101ff17d240eb298ebc65361d61b9799a

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.097230Z digest=sha256:5377068f9907203250cc4713c920e72d8ec35da4248c0107de252b3b9a6e1bf9

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=sha256:354605f3a49b66048816ae5d76b6da9612507664ea8d5ae8ce24854f341653a1

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.110255Z digest=sha256:cbe9a5f3e5091e4d5a90a6b78eeec5fa0b412e87bf68b410277d26bd6141c676

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.114094Z digest=sha256:e459fad10af7447632596969a28538d14e0fe42bcca912843284a3ab858a36d7

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.117438Z digest=sha256:ddffb601fa265c8efd9830591c753bb955887b8cba5bdbdb584deceb8fd8d66d

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.120929Z digest=sha256:31490788d99bbadb72d8f53303c07ff73a61bf5003500366a6ad433fdd3d9110

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=sha256:550452e5104e4b571ed8f76e7977078cd98fe7059526880b4689f12758f2b944

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.128485Z digest=sha256:651bbecb529b4d8b16bd318b8d3ce97d4a719de124077a8bdc8267964354725e

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.131938Z digest=sha256:08a2dfa3223869bfce3a4bf048ded71a1d0b92c4da38128b25ca551b04303f69

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.135888Z digest=sha256:35d695a404d05b4bf8be0fd1f1a5ec88bb8ebf3c6496712a27047be9048b9270

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.139463Z digest=sha256:4d78d63eb311c38d3ab35ddb2fed058e7481363506a1448e58cdd8ebee839f37

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.143131Z digest=sha256:d9c07c3ff59b7371bc77761a6c7c53368d6d2e46541352cc251ab246ceac4105

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.151106Z digest=sha256:08db8fa514e44f57bdeb4d56d0e703d059cf4b3bb54efdaeb76444c1276ca7a0

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.154728Z digest=sha256:1be8abb49338d34fb635220bfedc5a6a4e1b2a098163d5a8a2f710fed5484421

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.158684Z digest=sha256:ed4dba3477f40618d6bb5e84d1cb3f339ff7272402477584a95edb3682587f1e

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.171053Z digest=sha256:d721a81cefd75ca28c9ee5d208f29a6cf81b8a2e6522c30855d120ffd23ca576

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:ba85362646d0de1df6aa2420dc732d477c3787da4a418c52b6dcd60cfa4e2200

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=sha256:5f8d8c8bba7d9e93ed9f31da588278b31c934f2fe0b01cae90efc161e78da416

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=sha256:3b25dea57bda32db11a98c26a0a24308cd0fe40add30660113eb92dbd8556e34

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=sha256:401b24f0da63fc7d679c0e7d7d5561276babaf323ad1349b4fe57a41b6db8d72

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:e381e2835877f7387ac5b70920997678ade05d37e9de3a672c129bea52877c02

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.196000Z digest=sha256:4c657b9b78ac6c4ce5151b418a5e1fd53411840e345dd96ffc8e9764f21fd1f2

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.199730Z digest=sha256:952a2157c1dd08dcd18c4040021267aaa16d17b52b9bebc6fcebf2e809460da2

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:dfc7750109541cdb7b19930f74449ccd5a792ef2900230d77244bef87e54150d

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.207415Z digest=sha256:e4c0a2a88d2521d394361c98bff6a4278411d39f542f611f160e995f7d5fc5e9

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.211108Z digest=sha256:5bc833200bcbcc3391a20bcb96101244fe3caa7b395b3adb7ac8ca2f1339d0b8

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.214869Z digest=sha256:571f41e356ce7933de47a38281f232e433ee2f8e3122657b1e0349d631783aac

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.218831Z digest=sha256:b1daef2426f9138300129f0772f6d0d04acd6f196ad0ebf0bc8533822e6a5fa7

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=sha256:0ebdba2f4c4a3aaf49eb6f6581bd9de037ac556b27663ed8af0d6586c06c56e1

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.226712Z digest=sha256:6f456a71198c9d67b23299446d6e90bdb2083a661cf5c44e55bbb545a921b376

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.230464Z digest=sha256:f808c5c8bee85a957d879624cdce295d6522304eaa75010d855443f4868455ae

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.234730Z digest=sha256:3c9543146044d14abf48c7839737ac2ea5b1bdc52654abb8c6772e868e42a6de

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.238772Z digest=sha256:83f0f7efca758c98c2d33bfca60d28e2b3eacf9e18d05ff2137067ad6b7a37a7

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.242432Z digest=sha256:9d72d5d191d5263bd16e93c1106491eb22692877146f355979a817a67e60960f

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=sha256:7c995dbb2c7243ea57ed6132215e90169bfd1688b7bc0ebc4b0863d22500cd01

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.249932Z digest=sha256:f1baa17035a7174800244cdc133e85951119d3a24118f65a7c9c5220963652f1

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.253911Z digest=sha256:0ca97814d0b389cfa343b7e2cf0459f3310dda81ba515d15615f1e68d296c468

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=sha256:189fecbb0c42cd15a2bb4a78d84b8b80ab0a9b759293b5b7d4123a6f65d8c7c5

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.261497Z digest=sha256:763ee2c7fff8c202253a994946280d67743ee7d41906ab6859d3f3bfb26184e6

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.265417Z digest=sha256:1b9bb26cee4dc8d4681a16bcd8d6a882b2514265443effa34ae4bb27081467ba

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.269514Z digest=sha256:535aacf45ceb46ae398717e4182f9188c776522a70990dd008b46470ba769d41

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.273929Z digest=sha256:1a59aea38d5ba00075eaf96c590e21070c95cf2d4b3f7e920ef063cfbc44f397

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.277974Z digest=sha256:58a242454abb44e42ebe21e29a65e06b3e37c460123b0bc4a6eb8139f3af262c

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.281827Z digest=sha256:1c6a25658ad3be7c0606bbef622710504c6e900afe25def6ccecf259ab4778a3

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.285536Z digest=sha256:086065b6ee7e5e9676f752d68960e346fac700a49e26b26589a99a777cf7ab64

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.288965Z digest=sha256:3c42cc131c3978bfaee081b3537230178e65cbaa9f7b06a911655d7b5f32fdad

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.294994Z digest=sha256:9358a92a5b85e5500d0bba85c6c1e312f65b623b4a2e59a6fce0f181d332e43c

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:fed8d1dfee8b28c553ab28e36ba7033966619632f41de8d21041cfa0a0317d14

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=sha256:59d4b6baa5e72ccf3dcb9dcb119ea139b9b197dd07269f7b3a87a0f2965c98a2

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.307506Z digest=sha256:fa867d8df4140946356beda9f19862a894beac86626dbd8b6d2289b00fc1edab

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.311432Z digest=sha256:502acbd96979724d9782420cdf974200cd55488884ec3d1ac7b9723e8ff1d54e

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.314904Z digest=sha256:e638cde97daaa7f78a6a04f1b9df1f3efca78864b12a921de4b484807f8221a8

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.318569Z digest=sha256:1f84dbf451c12ce4e248e6df6d5416ac3504e15bae8c9122b88cd1805dc511cc

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.322057Z digest=sha256:6e2e99507e222f0b9796d0ad0ab5f3c8400ba862453a193588a940c6e26b8ad2

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=sha256:1e4ef3d7a189b12bda49f203be1483e13fae53d44cb1d352af830520052a9acb

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.329389Z digest=sha256:fcb8abad047c044ca5a95966cf246e8aafe88f21f93ff4144ab4075b7f6a0ba3

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.332860Z digest=sha256:4be7f507ea727754b3bbda9c65a9e0e69377774d453a37badf1ea32be9c06e5e

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.337589Z digest=sha256:7f650ada3adcd085e33d2e7b45cd48ac255db230a9704589703236b06c3c1f7c

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.342024Z digest=sha256:a02ef3ece7eba59507f1f132515b8d95e06b72e2fe6af114aef64cefa92aa548

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.345459Z digest=sha256:ddf284bf22ea5da5fbfe29bb13e1add68a8e8a0d96f6fa24c01f19d83717df51

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.349018Z digest=sha256:23057ffefd724165472e9605c1757a194a0d9b5be1b7db65bc9db2bf60324928

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.353038Z digest=sha256:09574daf1bf334a0e13bbac06e4021ea186574077cee11394225455d7c9deea2

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=sha256:511ccb99696164c3c204ffb82fdf0c297bc2c62ab1b1096322d2710209263d75

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.361144Z digest=sha256:9461019539970ca216ea61cc8cce9db6586991817f5f9474a7f8fe5c6ff688f7

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=sha256:477e226ef3ac74ba06ceb19ae75e8bfb6bb21644d49a8ee89c6a9fcc7a5a756a

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.369077Z digest=sha256:e950216d34525ddfa0bea61b483c08c64f5525f0141668a0071a932ad307be93

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.373215Z digest=sha256:498821387658124210534ae96dc39c6062b207c7ffe932a4c24aa4a3108da108

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.377052Z digest=sha256:d79ffdb8f9878b931ba362f01331810127c63ab7ce3e528a61e0bc180ff60407

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.380734Z digest=sha256:6687badbaa8db844626abcc3f026a111127842fb6e7041c5ce5bb0769674ff1f

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:f2d5a485d38d73ff188ec44ca09d5d09a5e2cbcaea99513700c429845488b39f

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.389222Z digest=sha256:f16cf1325f9bfbd75644550b30683a6bc137fb99ea597116f434849b64d1f328

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.393966Z digest=sha256:d9731e93854d827f73bac3068b635eb7d2781543141dc0a51d0b36bd64f7b791

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.398756Z digest=sha256:9c74779f52da35253f48421cc9c6ea75cf704ec873a0f5dded7be07a8539b7f9

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.402637Z digest=sha256:0731f342e25360bf95220fb1ab43095cdfc7d8c3792de976f409d683f80909bc

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.406325Z digest=sha256:d3fa7df4ce130f25b396297af7ad4660fd8fb42a8a96da0dd78f921b60c9712e

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.409887Z digest=sha256:919fc8c9f6ff2c46eb215534f1136652893bb415c03209cbc84cb25c57da6e92

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.413684Z digest=sha256:0dd5a4a690d5ce7cb00ddd9676f544ac0ee6ea2d947087f1b28213dac4f034ce

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.417360Z digest=sha256:02a5f6b64d2245861220b2f0585ed2abb1bd781a94b0492a1bf0caa31963ac53

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.421001Z digest=sha256:6d1070fec32ffc05ecdecd2202e3a7f2626a673b72a68d4f4ba36791f10183e6

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:56:50.424986Z digest=sha256:671813667c206ed2b0080d0990c88fb37304b5a310eb9ead9f7e2da6ec1f3a3d

Pith citing papers

No inbound Pith citation observations are available.