Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-03T15:10:09.077524Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 1 inbound Pith citation observation for arXiv:2512.18176.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-03T15:10:09.077524Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-04T01:14:35.222900Z
A source-named dated measurement, never combined with another source.
Source: cited_works
54 of 54 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 27ded3cd-a709-431a-b039-6e714e4ab934 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation V oxelmorph: a learning framework for deformable medical image registration.IEEE Transactions on Medical Imaging, 38(8):1788–1800, 2019
Reference 1
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a54c8952-39a1-4808-b340-3e2f72286be3 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Fam- net: Frequency-aware matching network for cross-domain few-shot medical image segmentation
Reference 2
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8b7c5187-3961-47df-a38c-9ca85e7dff02 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Uni- verseg: Universal medical image segmentation
Reference 3
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 02d01091-63f4-4be6-93da-c0df356a38da · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Few-shot medical image segmenta- tion via generating multiple representative descriptors.IEEE Transactions on Medical Imaging, 43(6):2202–2214, 2024
Reference 4
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c05911b6-4dbe-4d7e-b9ca-4bc18f5c77b2 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Utnet: a hy- brid transformer architecture for medical image segmentation
Reference 5
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6ad4401b-3b3e-4361-93a8-da42a3521122 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Show and segment: Universal medical image segmentation via in-context learning
Reference 6
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9d3cf86b-8cb6-4a87-a99a-e108ee138eb9 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation 3dsam-adapter: Holistic adaptation of sam from 2d to 3d for promptable tumor segmentation.Medical Image Analysis, 98:103324, 2024
Reference 7
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2902dc6e-94e2-4501-b234-aa81388c31ad · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Synth- morph: learning contrast-invariant registration without ac- quired images.IEEE Transactions on Medical Imaging, 41 (3):543–558, 2021
Reference 8
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2884bdd8-0f72-4bb0-8268-21f7e1a5099d · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Learning the ef- fect of registration hyperparameters with hypermorph.The Journal of Machine Learning for Biomedical Imaging, 1:003,
Reference 9
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7d04d478-5db3-4407-a7ab-fe11ef47bed7 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Icl-sam: Synergizing in-context learning model and sam in medical image segmentation
Reference 10
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f94f1895-97a5-4165-8a8d-94e7aa68bffc · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Multi-atlas seg- mentation of biomedical images: a survey.Medical Image Analysis, 24(1):205–219, 2015
Reference 11
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 905a0944-5171-40f8-ab0c-a223230ff7e7 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation nnu-net: a self-configuring method for deep learning-based biomedical image segmentation.Na- ture Methods, 18(2):203–211, 2021
Reference 12
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 86371618-2c2f-4547-80a5-4fd3860a4d12 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation nnInteractive: Redefining 3D Promptable Segmentation
Reference 13
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e3b82564-cd7a-4b3d-947f-c72a5c715020 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Chaos challenge-combined (ct-mr) healthy abdominal organ segmen- tation.Medical Image Analysis, 69:101950, 2021
Reference 14
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f4ad1b9a-bad1-4440-a10e-623b3200b9e4 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Segment any- thing
Reference 15
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b22049a9-3ce6-4662-baaf-1b049cbae29b · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Miccai multi-atlas la- beling beyond the cranial vault–workshop and challenge
Reference 16
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 593c8a21-b271-488f-b469-6993ce00af78 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Few shot medical image segmentation with cross attention transformer
Reference 17
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d8262efd-38e9-4a2c-9616-a9fce6430122 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Swin-umamba†: Adapting mamba-based vision foundation models for medical image segmentation.IEEE Transactions on Medical Imaging, 2024
Reference 18
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4c272082-2f5b-428e-b8ac-a482372c629b · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Segment anything in context with vision foundation models.International Journal of Computer Vision, 133(10): 7460–7485, 2025
Reference 19
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c7df4dde-5a0b-4b63-8d3f-ed479c8640aa · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Robust one-shot segmentation of brain tissues via image-aligned style transformation
Reference 20
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5d19069e-b766-4e21-a583-c6cad3114ec0 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Segment anything in medical images.Nature Communications, 15(1):654, 2024
Reference 21
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 86cfd2f3-cb85-4d60-98af-6b0b1e657f69 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation MedSAM2: Segment Anything in 3D Medical Images and Videos
Reference 22
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7b5b67fe-15b9-42b7-a356-535d2862650c · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation One polyp identifies all: One-shot polyp segmentation with sam via cascaded priors and iterative prompt evolution
Reference 23
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e03ccd48-a447-4186-95ea-7a11e66a8a74 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Unresolved cited work
Reference 24
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8594a942-adbf-483a-9ce8-05badae6a18a · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Cross-domain few- shot segmentation via iterative support-query correspondence mining
Reference 25
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b0bdb41d-bf19-4323-ac86-7dffe9682543 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation DINOv2: Learning Robust Visual Features without Supervision
Reference 26
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 97436f78-4548-42fd-881e-1d8069490448 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Self-supervised learning for few- shot medical image segmentation.IEEE Transactions on Medical Imaging, 41(7):1837–1848, 2022
Reference 27
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0ed3d489-2aba-41e3-a520-ce37cc4b0051 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Avt: Multicenter aortic vessel tree cta dataset collection with ground truth segmentation masks.Data in Brief, 40:107801, 2022
Reference 28
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation deb6773a-3fae-402c-8fb1-fff09e29dbc2 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Tyche: Stochastic in-context learning for medical image segmenta- tion
Reference 29
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bfd4f52b-8ad8-425c-839b-425bb7b33d99 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation SAM 2: Segment Anything in Images and Videos
Reference 30
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 06f2da32-5d73-4984-8a0b-b9211ce9520e · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation U-net: Convolutional networks for biomedical image segmentation
Reference 31
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fa613a34-b14c-4b7d-b9c3-16f273791fba · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Vm-unet: Vision mamba unet for medical image segmentation.ACM Transactions on Multimedia Computing, Communications and Applications, 2024
Reference 32
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ca392704-a3e7-4a8e-804a-0e208bb4568d · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Few-shot medical image segmentation with high-fidelity prototypes.Medical Image Analysis, 100:103412, 2025
Reference 33
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 08ca1205-57c6-43d1-8fc5-1b57fe549749 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Multi-atlas segmen- tation with joint label fusion.IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(3):611–623, 2012
Reference 34
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 05e79466-c84a-4f67-8281-b52b3ab62fa7 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Mixed trans- former u-net for medical image segmentation
Reference 35
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0a88a34a-b04a-4761-b77a-982d343facfd · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Sam-med3d: A vision foundation model for general-purpose segmentation on volumetric medical im- ages.IEEE Transactions on Neural Networks and Learning Systems, 2025
Reference 36
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5ba16194-7d3e-4157-a72b-b57052b23b20 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Seggpt: Towards segmenting everything in context
Reference 37
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3560364b-dbf9-4711-99b9-d563e8a7fae5 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation vesselfm: A foundation model for universal 3d blood vessel segmentation
Reference 38
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ad383e35-e339-4aa1-9ba4-aa1a90494654 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Scribbleprompt: fast and flexible interactive segmen- tation for any biomedical image
Reference 39
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 20d8c8d0-e252-4749-a24c-bcb82c62c49e · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Multiverseg: Scalable interactive segmenta- tion of biomedical imaging datasets with in-context guidance
Reference 40
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 90e1c7d4-5b67-4812-a25d-04a2b50c17af · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation One-prompt to segment all medical images
Reference 41
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7ddcccfe-76a4-4ba4-9efc-e51faf1f2bc6 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Eicseg: Universal medical image segmentation via explicit in-context learning.IEEE Transactions on Medical Imaging, 2025
Reference 42
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6522f400-005a-47d4-b532-4e88b7596042 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Segmamba: Long-range sequential modeling mamba for 3d medical image segmentation
Reference 43
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5c1694ef-ccae-4975-b50e-25655818cca7 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Unlocking the power of sam 2 for few-shot segmentation
Reference 44
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 18cb0946-b6bd-4d24-8933-6d1a544839f2 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Mapseg: Unified unsupervised domain adaptation for heterogeneous medical image segmentation based on 3d masked autoencoding and pseudo-labeling
Reference 45
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 92bad3c1-1232-4198-8104-5555fd91ed24 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Segmic: A universal model for medical image segmentation through in-context learning.Pattern Recognition, page 112179, 2025
Reference 46
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 345805e4-bf6f-46dc-871d-ccc3f24461b5 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation nn- former: V olumetric medical image segmentation via a 3d transformer.IEEE Transactions on Image Processing, 32: 4036–4045, 2023
Reference 47
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d8b463e8-2ebf-4998-b283-4aa4dd0bec4c · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Unet++: Redesigning skip connections to exploit multiscale features in image segmen- tation.IEEE Transactions on Medical Imaging, 39(6):1856– 1867, 2019
Reference 48
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation da911141-eeba-4d3e-8c43-6c817840d1fa · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Maup: Training-free multi-center adaptive uncertainty-aware prompting for cross- domain few-shot medical image segmentation
Reference 49
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 079d1b4b-96d2-4926-8aaf-2a12a092f374 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Few-shot medical image segmentation via a region-enhanced prototypical transformer
Reference 50
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 18d3e596-db3b-4195-a5dd-ac6a166be0f5 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Different FMs exhibit varying sensitivities to prompt types (e.g., points, boxes, or dense masks) based on their pretraining objectives and architecture
Reference 51
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 657bc00c-8982-456c-a623-28ca7bae8ad6 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation Unresolved cited work
Reference 52
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5be2cc5f-60a2-41b0-b519-90fb46d8b73f · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation However, their 2D architectures struggle to effectively cap- ture the full spatial context required for accurate segmen- tation in 3D medical data
Reference 53
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8b6b7171-3ef2-4454-bbb8-393fc6bc3730 · outbound
Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation In our method, we employ a deep-learning- based test-time optimization strategy derived from V ox- elMorph [ 1]
Reference 54
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 562b85a9-4dac-4745-82d6-264df8e38ab7 · inbound
Automatic LV Localization and Short-Axis Plane Estimation from Arbitrary CMR Slice Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation
Reference 27
Source-reported events for the cited work
Unavailable: canonical work link unavailable.