Vessel segmentation for X-separation | Paper Citation Record

Observation 467ada35-d157-4058-b575-d8d1d260edd1 · outbound

This paper cites vesselness.

Vessel segmentation for X-separation vesselness

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:56:52.537956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6389a743-ea95-4fda-b2ee-e187b667b520 · outbound

This paper cites vesselness.

Vessel segmentation for X-separation vesselness

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:56:52.527017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6fce740b-5d54-4311-933f-87aff10df160 · outbound

This paper cites 2 for 𝜒𝑝𝑎𝑟𝑎 and Fig.

Vessel segmentation for X-separation 2 for 𝜒𝑝𝑎𝑟𝑎 and Fig

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:56:52.516267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ff1faf53-0d6f-4feb-a7a4-4e4e1c58c82f · outbound

This paper cites The proposed method significantly reduces both processing time and memory usage compared to the GRE -based vessel segmentation method.

Vessel segmentation for X-separation The proposed method significantly reduces both processing time and memory usage compared to the GRE -based vessel segmentation method

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:56:52.505033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 12402e91-9871-4fe5-83df-4e623fa659ed · outbound

This paper cites an unresolved cited work.

Vessel segmentation for X-separation Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-09T16:56:52.493483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 05c3b4bc-3d31-40aa-b7de-d858ab6d3b7b · outbound

This paper cites an unresolved cited work.

Vessel segmentation for X-separation Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-09T16:56:52.482391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fcb3aa58-0adb-4379-8a6e-030d27c398d6 · outbound

This paper cites Magnetic Resonance of Myelin Water: An in vivo Marker for Myelin.

Vessel segmentation for X-separation Magnetic Resonance of Myelin Water: An in vivo Marker for Myelin

Reference 7

Resolution: verified exact; doi, observed 2026-08-09T16:56:48.890544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a173d133-0576-49df-bfcb-f30a43951d0b · outbound

This paper cites The role of iron in brain ageing and neurodegenerative disorders.

Vessel segmentation for X-separation The role of iron in brain ageing and neurodegenerative disorders

Reference 8

Resolution: malformed identifier; no resolver link, observed 2026-08-09T16:56:48.133934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf722577-4d0e-4703-a60d-6947e320923c · outbound

This paper cites Evidence of demyelination in mild cognitive impairment and dementia using a direct and specific magnetic resonance imaging measure of myelin content.

Vessel segmentation for X-separation Evidence of demyelination in mild cognitive impairment and dementia using a direct and specific magnetic resonance imaging measure of myelin content

Reference 9

Resolution: verified exact; doi, observed 2026-08-09T16:56:48.872920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7b752fff-581a-4896-ae3c-5b538c2e0071 · outbound

This paper cites Cortical Iron Reflects Severity of Alzheimer’s Disease.

Vessel segmentation for X-separation Cortical Iron Reflects Severity of Alzheimer’s Disease

Reference 10

Resolution: verified exact; doi, observed 2026-08-09T16:56:48.861813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 30c740ed-e0b2-48a3-bc9c-dc91f13d1acd · outbound

This paper cites Iron, Myelin, and the Brain: Neuroimaging Meets Neurobiology.

Vessel segmentation for X-separation Iron, Myelin, and the Brain: Neuroimaging Meets Neurobiology

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-09T16:56:48.145156Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7769852a-3863-4bca-8cab-70382e1ac0b0 · outbound

This paper cites Iron in multiple sclerosis: roles in neurodegeneration and repair.

Vessel segmentation for X-separation Iron in multiple sclerosis: roles in neurodegeneration and repair

Reference 12

Resolution: verified exact; doi, observed 2026-08-09T16:56:48.843900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 602663a1-9fe3-4314-9822-318737ed5629 · outbound

This paper cites Iron, brain ageing and neurodegenerative disorders.

Vessel segmentation for X-separation Iron, brain ageing and neurodegenerative disorders

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-09T16:56:48.152856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 56eba91c-5f12-4fa8-921a-7926728a5740 · outbound

This paper cites Separating positive and negative susceptibility sources in QSM.

Vessel segmentation for X-separation Separating positive and negative susceptibility sources in QSM

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:56:52.471481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e915e540-7609-4e89-aba4-820d24b7a8eb · outbound

This paper cites χ-separation: Magnetic susceptibility source separation toward iron and myelin mapping in the brain.

Vessel segmentation for X-separation χ-separation: Magnetic susceptibility source separation toward iron and myelin mapping in the brain

Reference 15

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-09T16:56:52.393778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f999c0e2-4bed-4c1e-bec7-275b3d26952d · outbound

This paper cites Comparison between R2′‐based and R2*‐based χ‐separation methods: A clinical evaluation in individuals with multiple sclerosis.

Vessel segmentation for X-separation Comparison between R2′‐based and R2*‐based χ‐separation methods: A clinical evaluation in individuals with multiple sclerosis

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-09T16:56:48.163765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e5b58f9-b8bc-494d-94a5-005e684e6996 · outbound

This paper cites Quantitative susceptibility mapping with source separation in normal brain development of newborns.

Vessel segmentation for X-separation Quantitative susceptibility mapping with source separation in normal brain development of newborns

Reference 17

Resolution: verified exact; doi, observed 2026-08-09T16:56:48.819889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 29dca304-2f0b-4c10-bd20-8fa47087bb00 · outbound

This paper cites Quantifying Remyelination Using χ-Separation in White Matter and Cortical Multiple Sclerosis Lesions.

Vessel segmentation for X-separation Quantifying Remyelination Using χ-Separation in White Matter and Cortical Multiple Sclerosis Lesions

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-09T16:56:48.170576Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9ecd3427-a5cb-49fc-9935-9a28387349ee · outbound

This paper cites Quantitative susceptibility mapping analyses of white matter in Parkinson’s disease using susceptibility separation technique.

Vessel segmentation for X-separation Quantitative susceptibility mapping analyses of white matter in Parkinson’s disease using susceptibility separation technique

Reference 19

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-09T16:56:52.067979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7e24a289-6e0c-4ed7-b123-d52bbbfa70de · outbound

This paper cites MR Susceptibility Separation for Quantifying Lesion Paramagnetic and Diamagnetic Evolution in Relapsing–Remitting Multiple Sclerosis.

Vessel segmentation for X-separation MR Susceptibility Separation for Quantifying Lesion Paramagnetic and Diamagnetic Evolution in Relapsing–Remitting Multiple Sclerosis

Reference 20

Resolution: verified exact; doi, observed 2026-08-09T16:56:48.802345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation bd08d314-bc7c-4f78-9daa-93e1ee0c56b3 · outbound

This paper cites Quantitative magnetic resonance imaging biomarkers for cortical pathology in multiple sclerosis at 7 T.

Vessel segmentation for X-separation Quantitative magnetic resonance imaging biomarkers for cortical pathology in multiple sclerosis at 7 T

Reference 21

Resolution: verified exact; doi, observed 2026-08-09T16:56:48.791316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e460cc45-a04d-43e1-82cf-7c9a6cf08018 · outbound

This paper cites χ-Separation Imaging for Diagnosis of Multiple Sclerosis versus Neuromyelitis Optica Spectrum Disorder.

Vessel segmentation for X-separation χ-Separation Imaging for Diagnosis of Multiple Sclerosis versus Neuromyelitis Optica Spectrum Disorder

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-09T16:56:48.184816Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35f1caa2-fdf6-4f46-aaea-90040acc8f80 · outbound

This paper cites Decompose quantitative susceptibility mapping (QSM) to sub-voxel diamagnetic and paramagnetic components based on gradient-echo MRI data.

Vessel segmentation for X-separation Decompose quantitative susceptibility mapping (QSM) to sub-voxel diamagnetic and paramagnetic components based on gradient-echo MRI data

Reference 23

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-09T16:56:51.840765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fc9a0828-3a43-46c6-bdd5-5b5e2ada25ab · outbound

This paper cites an unresolved cited work.

Vessel segmentation for X-separation Unresolved cited work

Reference 24

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-09T16:56:51.620467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 340f4ca9-fafa-4079-abca-f1676d1ff22c · outbound

This paper cites APART-QSM: An improved sub-voxel quantitative susceptibility mapping for susceptibility source separation using an iterative data fitting method.

Vessel segmentation for X-separation APART-QSM: An improved sub-voxel quantitative susceptibility mapping for susceptibility source separation using an iterative data fitting method

Reference 25

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-09T16:56:51.424295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2a16d058-d4da-4ebc-8322-110c2000fa6a · outbound

This paper cites Quantitative susceptibility mapping for susceptibility source separation with adaptive relaxometric constant estimation (QSM- ARCS) from solely gradient-echo data.

Vessel segmentation for X-separation Quantitative susceptibility mapping for susceptibility source separation with adaptive relaxometric constant estimation (QSM- ARCS) from solely gradient-echo data

Reference 26

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-09T16:56:51.260639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d8dc40c8-0191-4a8f-a5a4-411c19b5bfeb · outbound

This paper cites So You Want to Image Myelin Using MRI: Magnetic Susceptibility Source Separation for Myelin Imaging.

Vessel segmentation for X-separation So You Want to Image Myelin Using MRI: Magnetic Susceptibility Source Separation for Myelin Imaging

Reference 27

Resolution: verified exact; doi, observed 2026-08-09T16:56:48.773644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3a8aa0b0-2cac-46a4-87ed-8cd366aadfa2 · outbound

This paper cites R mapping in the presence of macroscopic B0 field variations.

Vessel segmentation for X-separation R mapping in the presence of macroscopic B0 field variations

Reference 28

Resolution: verified exact; doi, observed 2026-08-09T16:56:48.762058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 30483991-c81a-4ffb-b66d-22ecaa6902b5 · outbound

This paper cites Voxel spread function method for correction of magnetic field inhomogeneity effects in quantitative gradient‐echo‐based MRI.

Vessel segmentation for X-separation Voxel spread function method for correction of magnetic field inhomogeneity effects in quantitative gradient‐echo‐based MRI

Reference 29

Resolution: verified exact; doi, observed 2026-08-09T16:56:48.751410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 052d5b5b-fcc7-4ed1-bf61-422b16bab93e · outbound

This paper cites Spatial Misregistration of Vascular flow during MR imaging of the CNS.

Vessel segmentation for X-separation Spatial Misregistration of Vascular flow during MR imaging of the CNS

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:56:52.459588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9cd9d4bb-0f8e-44a8-99b6-a36a44b376d3 · outbound

This paper cites On the nature and reduction of the displacement artifact in flow images.

Vessel segmentation for X-separation On the nature and reduction of the displacement artifact in flow images

Reference 31

Resolution: verified exact; doi, observed 2026-08-09T16:56:48.740571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0c18bcff-c515-4179-bb74-bba5ae13e43d · outbound

This paper cites Depth-wise profiles of iron and myelin in the cortex and white matter using χ-separation: A preliminary study.

Vessel segmentation for X-separation Depth-wise profiles of iron and myelin in the cortex and white matter using χ-separation: A preliminary study

Reference 32

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-09T16:56:51.103565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 37d96046-eff5-40a8-9eea-35f757f8bfe2 · outbound

This paper cites A human brain atlas of χ‐separation for normative iron and myelin distributions.

Vessel segmentation for X-separation A human brain atlas of χ‐separation for normative iron and myelin distributions

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-09T16:56:48.223237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab856bc8-0da0-4352-916d-5d278972c7af · outbound

This paper cites Vessel Segmentation from Quantitative Susceptibility Maps for Local Oxygenation Venography.

Vessel segmentation for X-separation Vessel Segmentation from Quantitative Susceptibility Maps for Local Oxygenation Venography

Reference 34

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-09T16:56:50.816854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ef17784d-7e70-4e92-af0c-d53ed3c59776 · outbound

This paper cites Investigating the effect of flow compensation and quantitative susceptibility mapping method on the accuracy of venous susceptibility measurement.

Vessel segmentation for X-separation Investigating the effect of flow compensation and quantitative susceptibility mapping method on the accuracy of venous susceptibility measurement

Reference 35

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-09T16:56:50.639272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e7f8bce0-e40b-4fb1-b3af-4e94e07126b3 · outbound

This paper cites Investigating the oxygenation of brain arteriovenous malformations using quantitative susceptibility mapping.

Vessel segmentation for X-separation Investigating the oxygenation of brain arteriovenous malformations using quantitative susceptibility mapping

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:56:52.448800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c3e37087-7f34-4c9f-80f4-c3d0c2090411 · outbound

This paper cites Improved susceptibility‐weighted imaging for high contrast and resolution thalamic nuclei mapping at 7T.

Vessel segmentation for X-separation Improved susceptibility‐weighted imaging for high contrast and resolution thalamic nuclei mapping at 7T

Reference 37

Resolution: verified exact; doi, observed 2026-08-09T16:56:48.645979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 35d33e20-6b09-4bd9-be07-4eec11f8ec4d · outbound

This paper cites Quantification of cerebral veins in patients with acute migraine with aura: A fully automated quantification algorithm using susceptibility-weighted imaging.

Vessel segmentation for X-separation Quantification of cerebral veins in patients with acute migraine with aura: A fully automated quantification algorithm using susceptibility-weighted imaging

Reference 38

Resolution: verified exact; doi, observed 2026-08-09T16:56:48.712964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 44ba19b7-1886-4ede-bd17-f033e4c5a87e · outbound

This paper cites Diminished visibility of cerebral venous vasculature in multiple sclerosis by susceptibility‐weighted imaging at 3.0 Tesla.

Vessel segmentation for X-separation Diminished visibility of cerebral venous vasculature in multiple sclerosis by susceptibility‐weighted imaging at 3.0 Tesla

Reference 39

Resolution: verified exact; doi, observed 2026-08-09T16:56:48.701994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b4a4dae5-05d4-4a93-b91d-dffd344e9869 · outbound

This paper cites MR venography of the human brain using susceptibility weighted imaging at very high field strength.

Vessel segmentation for X-separation MR venography of the human brain using susceptibility weighted imaging at very high field strength

Reference 40

Resolution: verified exact; doi, observed 2026-08-09T16:56:48.690409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b079a6e5-51b4-41b2-9a28-6082b4e6a536 · outbound

This paper cites Evaluation of SWI in Children with Sickle Cell Disease.

Vessel segmentation for X-separation Evaluation of SWI in Children with Sickle Cell Disease

Reference 41

Resolution: verified exact; doi, observed 2026-08-09T16:56:48.679240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6e1e27dc-8945-44e3-8539-78046e65e730 · outbound

This paper cites Deep learning based vein segmentation from susceptibility-weighted images.

Vessel segmentation for X-separation Deep learning based vein segmentation from susceptibility-weighted images

Reference 42

Resolution: verified exact; doi, observed 2026-08-09T16:56:48.667971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8456c521-1c26-4184-a7db-71b40577cc65 · outbound

This paper cites Quantification of brain oxygen extraction fraction using QSM and a hyperoxic challenge.

Vessel segmentation for X-separation Quantification of brain oxygen extraction fraction using QSM and a hyperoxic challenge

Reference 43

Resolution: verified exact; doi, observed 2026-08-09T16:56:48.657033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 05eb073a-49bf-4920-9ede-ebfdee8ce081 · outbound

This paper cites A novel gradient echo data based vein segmentation algorithm and its application for the detection of regional cerebral differences in venous susceptibility.

Vessel segmentation for X-separation A novel gradient echo data based vein segmentation algorithm and its application for the detection of regional cerebral differences in venous susceptibility

Reference 44

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-09T16:56:49.847861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fb016fc6-9a2b-477b-b969-026b8835626c · outbound

This paper cites Multiscale vessel enhancement filtering.

Vessel segmentation for X-separation Multiscale vessel enhancement filtering

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-09T16:56:48.266258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 056b62d8-9407-4d13-8a22-a992d9bbbcb9 · outbound

This paper cites Vessel enhancing diffusion A scale space representation of vessel structures.

Vessel segmentation for X-separation Vessel enhancing diffusion A scale space representation of vessel structures

Reference 46

Resolution: verified exact; doi, observed 2026-08-09T16:56:48.628199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f0bb52dd-6f20-4e23-81a0-cde474cae407 · outbound

This paper cites Enhancement of Vascular Structures in 3D and 2D Angiographic Images.

Vessel segmentation for X-separation Enhancement of Vascular Structures in 3D and 2D Angiographic Images

Reference 47

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-09T16:56:50.404357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 03357f27-69f6-4732-925a-78f567ac2ea7 · outbound

This paper cites 2D and 3D Vascular Structures Enhancement via Multiscale Fractional Anisotropy Tensor.

Vessel segmentation for X-separation 2D and 3D Vascular Structures Enhancement via Multiscale Fractional Anisotropy Tensor

Reference 48

Resolution: verified exact; local_arxiv, observed 2026-08-09T16:56:48.616841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e533f83c-b054-4112-a27f-1bfb77d1fa2a · outbound

This paper cites 2D and 3D Vascular Structures Enhancement Via Improved Vesselness Filter and Vessel Enhancing Diffusion.

Vessel segmentation for X-separation 2D and 3D Vascular Structures Enhancement Via Improved Vesselness Filter and Vessel Enhancing Diffusion

Reference 49

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-09T16:56:50.203073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e0045336-5f93-495b-b2c6-2b1113822c5c · outbound

This paper cites MAVEN: An Algorithm for Multi-Parametric Automated Segmentation of Brain Veins From Gradient Echo Acquisitions.

Vessel segmentation for X-separation MAVEN: An Algorithm for Multi-Parametric Automated Segmentation of Brain Veins From Gradient Echo Acquisitions

Reference 50

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-09T16:56:50.029380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d5aac6c1-56ad-4c23-a867-8202a00dfa65 · outbound

This paper cites Fast robust automated brain extraction.

Vessel segmentation for X-separation Fast robust automated brain extraction

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-09T16:56:48.312443Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a91fca36-223f-42f5-a248-bfc3822a2043 · outbound

This paper cites Background-Suppressed MR Venography of the Brain Using Magnitude Data: A High-Pass Filtering Approach.

Vessel segmentation for X-separation Background-Suppressed MR Venography of the Brain Using Magnitude Data: A High-Pass Filtering Approach

Reference 52

Resolution: verified exact; doi, observed 2026-08-09T16:56:48.602780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c60b446d-f1a4-41c1-be3d-cd3589e06679 · outbound

This paper cites Fast Image Inpainting Based on Coherence Transport.

Vessel segmentation for X-separation Fast Image Inpainting Based on Coherence Transport

Reference 53

Resolution: verified exact; doi, observed 2026-08-09T16:56:48.591571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ceadc492-c201-4e5d-957d-8152b28871fb · outbound

This paper cites Preliminary study of time maximum intensity projection computed tomography imaging for the detection of early ischemic change in patient with acute ischemic stroke.

Vessel segmentation for X-separation Preliminary study of time maximum intensity projection computed tomography imaging for the detection of early ischemic change in patient with acute ischemic stroke

Reference 54

Resolution: verified exact; doi, observed 2026-08-09T16:56:48.580702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation cde0df01-200b-4736-882f-a7012970d73e · outbound

This paper cites A coronary artery segmentation method based on multiscale analysis and region growing.

Vessel segmentation for X-separation A coronary artery segmentation method based on multiscale analysis and region growing

Reference 55

Resolution: verified exact; doi, observed 2026-08-09T16:56:48.570151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation af42bf98-7a8a-4193-b0a5-b677aa46169d · outbound

This paper cites χ‐sepnet: Deep Neural Network for Magnetic Susceptibility Source Separation.

Vessel segmentation for X-separation χ‐sepnet: Deep Neural Network for Magnetic Susceptibility Source Separation

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-09T16:56:48.305391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb4f5a02-6eeb-440a-bddf-6bcc087ec749 · outbound

This paper cites In-vivo high-resolution \chi-separation at 7T.

Vessel segmentation for X-separation In-vivo high-resolution \chi-separation at 7T

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:56:52.438229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5707f1fb-9b9f-4e89-8374-f392b0ab4b5b · outbound

This paper cites StimFit: A Toolbox for Robust T2 Mapping with Stimulated Echo Compensation.

Vessel segmentation for X-separation StimFit: A Toolbox for Robust T2 Mapping with Stimulated Echo Compensation

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:56:52.427509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f206e2c3-546f-4cf8-96ae-c278fa48cfb0 · outbound

This paper cites Recommended implementation of quantitative susceptibility mapping for clinical research in the brain: A consensus of the ISMRM electro‐magnetic tissue properties study group.

Vessel segmentation for X-separation Recommended implementation of quantitative susceptibility mapping for clinical research in the brain: A consensus of the ISMRM electro‐magnetic tissue properties study group

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-09T16:56:48.316235Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f2d12df-eeac-457f-9048-5632f2e4cd13 · outbound

This paper cites Phase unwrapping with a rapid opensource minimum spanning tree algorithm (ROMEO).

Vessel segmentation for X-separation Phase unwrapping with a rapid opensource minimum spanning tree algorithm (ROMEO)

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-09T16:56:48.319871Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f36fc68-25df-4dc7-9540-dd2c0e2f41a2 · outbound

This paper cites Fast and tissue-optimized mapping of magnetic susceptibility and T2* with multi-echo and multi-shot spirals.

Vessel segmentation for X-separation Fast and tissue-optimized mapping of magnetic susceptibility and T2* with multi-echo and multi-shot spirals

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-09T16:56:48.323333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 558069da-ab5d-484a-9ce3-1f1d1633ce0c · outbound

This paper cites Quantitative imaging of intrinsic magnetic tissue properties using MRI signal phase: An approach to in vivo brain iron metabolism? NeuroImage.

Vessel segmentation for X-separation Quantitative imaging of intrinsic magnetic tissue properties using MRI signal phase: An approach to in vivo brain iron metabolism? NeuroImage

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-09T16:56:48.326759Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7b68fe8-fd4a-40e3-b1b2-05d0d093f7d6 · outbound

This paper cites Whole brain susceptibility mapping using compressed sensing.

Vessel segmentation for X-separation Whole brain susceptibility mapping using compressed sensing

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-09T16:56:48.330284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20440f72-4b67-476c-8a55-e0d936ce8799 · outbound

This paper cites Transverse relaxometry with stimulated echo compensation.

Vessel segmentation for X-separation Transverse relaxometry with stimulated echo compensation

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-09T16:56:48.333848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a3a70ed-d0a4-4c18-a1c9-12ac852ad0f7 · outbound

This paper cites Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions.

Vessel segmentation for X-separation Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions

Reference 65

Resolution: verified exact; doi, observed 2026-08-09T16:56:48.468279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7b2cb6e3-207f-4b6f-af08-f8163a7c3303 · outbound

This paper cites Advances in functional and structural MR image analysis and implementation as FSL.

Vessel segmentation for X-separation Advances in functional and structural MR image analysis and implementation as FSL

Reference 66

Resolution: verified exact; doi, observed 2026-08-09T16:56:48.507468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b021c15e-0dc4-43f7-ace4-f4704fe902bf · outbound

This paper cites chi-separation using multi-orientation data in invivo and exvivo brains: Visualization of histology up to the resolution of 350 um.

Vessel segmentation for X-separation chi-separation using multi-orientation data in invivo and exvivo brains: Visualization of histology up to the resolution of 350 um

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:56:52.416957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3ac6ed47-2f8e-471d-9045-00142b714ae7 · outbound

This paper cites User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability.

Vessel segmentation for X-separation User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-09T16:56:48.348108Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38d2cc12-5aef-49ed-b50b-605b295b0fa2 · outbound

This paper cites Measures of the amount of ecologic association between species.

Vessel segmentation for X-separation Measures of the amount of ecologic association between species

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:56:52.404845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b20d2fde-a9d1-4ead-a318-9b430846c849 · outbound

This paper cites MRI estimates of brain iron concentration in normal aging using quantitative susceptibility mapping.

Vessel segmentation for X-separation MRI estimates of brain iron concentration in normal aging using quantitative susceptibility mapping

Reference 70

Resolution: verified exact; doi, observed 2026-08-09T16:56:48.489306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 48986852-ec27-4409-9c93-4ac6eaf52967 · outbound

This paper cites Iron Deposition in Brain: Does Aging Matter? Int J Mol Sci.

Vessel segmentation for X-separation Iron Deposition in Brain: Does Aging Matter? Int J Mol Sci

Reference 71

Resolution: verified exact; doi, observed 2026-08-09T16:56:48.478860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 72171da9-e0bd-4ac4-98e7-111ee11b8245 · outbound

This paper cites Segment anything in medical images.

Vessel segmentation for X-separation Segment anything in medical images

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-09T16:56:48.386143Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae6d3a2c-f255-4823-b11b-25e0de400220 · outbound

This paper cites Image Segmentation Using Deep Learning: A Survey.

Vessel segmentation for X-separation Image Segmentation Using Deep Learning: A Survey

Reference 73

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-09T16:56:49.678528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3a96567a-2ade-40e6-9b32-ab3d00c7b0f2 · outbound

This paper cites Medical image segmentation using deep learning: A survey.

Vessel segmentation for X-separation Medical image segmentation using deep learning: A survey

Reference 74

Resolution: verified exact; doi, observed 2026-08-09T16:56:48.457166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b068ed55-fe9f-4afe-8324-3f6aa0906b0c · outbound

This paper cites DeepVesselNet: Vessel Segmentation, Centerline Prediction, and Bifurcation Detection in 3-D Angiographic Volumes.

Vessel segmentation for X-separation DeepVesselNet: Vessel Segmentation, Centerline Prediction, and Bifurcation Detection in 3-D Angiographic Volumes

Reference 75

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-09T16:56:49.493433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 609e1f83-2210-427e-80c9-ec73737f6473 · outbound

This paper cites BRAVE-NET: Fully Automated Arterial Brain Vessel Segmentation in Patients With Cerebrovascular Disease.

Vessel segmentation for X-separation BRAVE-NET: Fully Automated Arterial Brain Vessel Segmentation in Patients With Cerebrovascular Disease

Reference 76

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-09T16:56:49.290060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 80d9eca3-74ba-49c4-a73a-c3afd0da7bfb · outbound

This paper cites Brain Vessel Segmentation Using Deep Learning—A Review.

Vessel segmentation for X-separation Brain Vessel Segmentation Using Deep Learning—A Review

Reference 77

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-09T16:56:49.125581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation dccc294a-4632-4d63-bb05-f4dc4fdcbbf4 · outbound

This paper cites Overview of quantitative susceptibility mapping using deep learning: Current status, challenges and opportunities.

Vessel segmentation for X-separation Overview of quantitative susceptibility mapping using deep learning: Current status, challenges and opportunities

Reference 78

Resolution: verified exact; doi, observed 2026-08-09T16:56:48.445546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9cc3da7a-c016-48ab-95cb-b1f4916acc44 · outbound

This paper cites I-MedSAM: Implicit Medical Image Segmentation with Segment Anything.

Vessel segmentation for X-separation I-MedSAM: Implicit Medical Image Segmentation with Segment Anything

Reference 80

Resolution: verified exact; local_arxiv, observed 2026-08-09T16:56:48.426586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 116f8626-595c-48c1-a2de-13ba03f09a63 · outbound

This paper cites an unresolved cited work.

Vessel segmentation for X-separation Unresolved cited work

Reference 453

Resolution: verified exact; doi, observed 2026-08-09T16:56:48.722931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Reference resolution

Outbound references

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