Paper Citation Record · LEDGER

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion

As of 15 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2412.08315.

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

pith.paper-citation-record.v1
2412.08315 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T18:02:05.714832Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

32 of 32 outbound references displayed

verified exact1
verified fuzzy14
unresolved17
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ce905666-01f4-4345-b5e0-65cfedadd657 · outbound

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

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion nnu-net: a self-configuring method for deep learning-based biomedical image segmentation,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T18:02:05.620586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dadaae67-41d3-4177-bae2-3f6dea3f898d · outbound

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

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion Swin unetr: Swin transformers for semantic segmentation of brain tumors in mri images,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:02:05.983399Z

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 e2b047d2-17ac-4508-814a-0016dcd5c255 · outbound

This paper cites UNETR++: Delving into Efficient and Accurate 3D Medical Image Segmentation.

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion UNETR++: Delving into Efficient and Accurate 3D Medical Image Segmentation

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-11T18:02:05.627385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88488c8f-fad9-495d-aeeb-45960723773b · outbound

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

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion nn- former: V olumetric medical image segmentation via a 3d transformer,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:02:05.974580Z

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 c5db6f53-494c-40fd-ab5d-1155ca109379 · outbound

This paper cites Segment anything,.

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion Segment anything,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T18:02:05.633527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a606a7d-83e9-448b-94f4-bdfff8fe8eed · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T18:02:05.636605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df3962db-9a21-411c-a05a-27ad64e498f2 · outbound

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

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T18:02:05.639967Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 620a2dfa-4ccb-4cad-9fdb-ea3e564ad4e0 · outbound

This paper cites 3DSAM-adapter: Holistic adaptation of SAM from 2D to 3D for promptable tumor segmentation.

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion 3DSAM-adapter: Holistic adaptation of SAM from 2D to 3D for promptable tumor segmentation

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T18:02:05.642897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc934bae-6614-4e27-b170-25e3f7046c36 · outbound

This paper cites SAM-Med3D: Towards General-purpose Segmentation Models for Volumetric Medical Images.

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion SAM-Med3D: Towards General-purpose Segmentation Models for Volumetric Medical Images

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T18:02:05.646262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e60bc54f-ac64-4555-a757-97627b6adc20 · outbound

This paper cites Are transformers more robust than cnns?.

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion Are transformers more robust than cnns?

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:02:05.960001Z

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 683cecaa-b3f0-403e-8093-0d66c6388b9e · outbound

This paper cites Interactive medical image segmentation using deep learning with image-specific fine tuning,.

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion Interactive medical image segmentation using deep learning with image-specific fine tuning,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:02:05.950453Z

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 9352dd13-91a0-4ca5-8aaa-8d2c27ebde45 · outbound

This paper cites Quality-aware memory network for interactive volumetric image segmentation,.

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion Quality-aware memory network for interactive volumetric image segmentation,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:02:05.940448Z

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 ee180ca7-bfaa-49ec-9e2e-a0cd89a031b6 · outbound

This paper cites A hybrid propagation network for interactive volumetric image segmentation,.

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion A hybrid propagation network for interactive volumetric image segmentation,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:02:05.931226Z

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 921bc2a2-7ab5-4f35-aee6-8e35bdb85a97 · outbound

This paper cites Exploring Cycle Consistency Learning in Interactive Volume Segmentation.

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion Exploring Cycle Consistency Learning in Interactive Volume Segmentation

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-08-11T18:02:05.777446Z

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 9b780a7f-cde7-467b-826e-af2fc470f860 · outbound

This paper cites Rethinking space-time networks with improved memory coverage for efficient video object segmentation,.

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion Rethinking space-time networks with improved memory coverage for efficient video object segmentation,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:02:05.921985Z

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 959edcfb-9216-4437-96b7-933244664a10 · outbound

This paper cites Deepigeos: a deep interactive geodesic framework for medical image segmentation,.

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion Deepigeos: a deep interactive geodesic framework for medical image segmentation,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:02:05.912735Z

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 45c58f99-058e-45e4-8518-0f0b415c10b6 · outbound

This paper cites Xmem: Long-term video object segmentation with an atkinson-shiffrin memory model,.

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion Xmem: Long-term video object segmentation with an atkinson-shiffrin memory model,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T18:02:05.670327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92bb495b-22ca-4b71-9c99-b79a5a371092 · outbound

This paper cites Reviving iterative training with mask guidance for interactive segmentation,.

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion Reviving iterative training with mask guidance for interactive segmentation,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T18:02:05.673099Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c293206c-d3d7-4624-a8c1-acffaae18a01 · outbound

This paper cites Deep high-resolution representation learning for visual recognition,.

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion Deep high-resolution representation learning for visual recognition,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T18:02:05.675939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 263ddac7-ae28-4ad8-b1ac-296653406a5a · outbound

This paper cites iShape: A First Step Towards Irregular Shape Instance Segmentation.

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion iShape: A First Step Towards Irregular Shape Instance Segmentation

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T18:02:05.678702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10906621-ee99-4700-aa0f-3145812df0e6 · outbound

This paper cites Amos: A large-scale abdominal multi-organ benchmark for versatile medical image segmentation,.

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion Amos: A large-scale abdominal multi-organ benchmark for versatile medical image segmentation,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:02:05.888292Z

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 0712d3db-146d-4b71-a8ff-2d4b704fc686 · outbound

This paper cites Focalclick: Towards practical interactive image segmentation,.

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion Focalclick: Towards practical interactive image segmentation,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T18:02:05.684825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f8d32672-bdc3-4c42-9df0-f887581c4599 · outbound

This paper cites Microsoft coco: Common objects in context,.

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion Microsoft coco: Common objects in context,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-11T18:02:05.687629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4100455d-a46c-47df-8e19-d6ab9a7556cc · outbound

This paper cites Lvis: A dataset for large vocabulary instance segmentation,.

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion Lvis: A dataset for large vocabulary instance segmentation,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:02:05.868815Z

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 b2996316-24d2-41b8-b085-733e4fbef552 · outbound

This paper cites A large annotated medical image dataset for the development and evaluation of segmentation algorithms.

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion A large annotated medical image dataset for the development and evaluation of segmentation algorithms

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T18:02:05.693399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9350b7c8-675c-41c7-a93a-8617d5963754 · outbound

This paper cites The KiTS19 Challenge Data: 300 Kidney Tumor Cases with Clinical Context, CT Semantic Segmentations, and Surgical Outcomes.

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion The KiTS19 Challenge Data: 300 Kidney Tumor Cases with Clinical Context, CT Semantic Segmentations, and Surgical Outcomes

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-11T18:02:05.696804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68d5d53f-52ba-4924-8757-5681b03fb5d0 · outbound

This paper cites 2018 Robotic Scene Segmentation Challenge,.

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion 2018 Robotic Scene Segmentation Challenge,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:02:05.859490Z

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 b9443780-4b79-4045-88ce-7d66b14b922e · outbound

This paper cites Miccai multi-atlas labeling beyond the cranial vault–workshop and challenge,.

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion Miccai multi-atlas labeling beyond the cranial vault–workshop and challenge,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-11T18:02:05.702953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 410b276a-bfa7-493b-b1f3-8cd9bb31df46 · outbound

This paper cites Transbts: Mul- timodal brain tumor segmentation using transformer,.

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion Transbts: Mul- timodal brain tumor segmentation using transformer,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:02:05.845113Z

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 ed93859b-61f8-4ad8-aae1-cb9f182467da · outbound

This paper cites Self-supervised pre-training of swin transformers for 3d medical image analysis,.

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion Self-supervised pre-training of swin transformers for 3d medical image analysis,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:02:05.836113Z

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 3f5c9d58-85df-4c68-96a6-bcc7fd2c24fd · outbound

This paper cites 3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image Segmentation.

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion 3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image Segmentation

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-11T18:02:05.711914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fbabbe93-ba62-4f38-bb20-87514b16c315 · outbound

This paper cites Sam- med2d,.

Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion Sam- med2d,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:02:05.826947Z

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.

Pith citing papers

No inbound Pith citation observations are available.