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Paper Citation Record · LEDGER

AI-Driven MRI-based Brain Tumour Segmentation Benchmarking

As of 14 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2506.20786.

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

pith.paper-citation-record.v1
2506.20786 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:50:02.378084Z

measured 26 of 26 standing notices

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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

26 of 26 outbound references displayed

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External citation measurements

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Outbound references

Observation 84ce5fe2-8e0a-4c5c-b810-4d0b795230da · outbound

This paper cites Brain tumor segmentation based on region of interest-aided localization and segmentation U- Net,.

AI-Driven MRI-based Brain Tumour Segmentation Benchmarking Brain tumor segmentation based on region of interest-aided localization and segmentation U- Net,

Reference 1

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Observation 1668dfb4-c9ef-403f-b1a7-e7d302589714 · outbound

This paper cites The Medical Segmentation Decathlon,.

AI-Driven MRI-based Brain Tumour Segmentation Benchmarking The Medical Segmentation Decathlon,

Reference 2

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Observation f9532d0f-19da-4c53-9f6b-4039eba99ddc · outbound

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

AI-Driven MRI-based Brain Tumour Segmentation Benchmarking U-net: Convolutional networks for biomedical image segmentation,

Reference 3

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Observation d76a4049-29a4-47b5-b01f-0654632c5812 · outbound

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

AI-Driven MRI-based Brain Tumour Segmentation Benchmarking nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation,

Reference 4

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Observation 59f24e5e-f717-416b-b58d-0321cbc8fdeb · outbound

This paper cites Medical Image Segmentation Review: The Success of U- Net,.

AI-Driven MRI-based Brain Tumour Segmentation Benchmarking Medical Image Segmentation Review: The Success of U- Net,

Reference 5

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Observation c0d7b9ee-c782-473f-8025-45dde59a1165 · outbound

This paper cites Segment Anything,.

AI-Driven MRI-based Brain Tumour Segmentation Benchmarking Segment Anything,

Reference 6

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Observation d81ec44f-0189-4bda-bf24-0475db5befd9 · outbound

This paper cites Segment anything in medical images,.

AI-Driven MRI-based Brain Tumour Segmentation Benchmarking Segment anything in medical images,

Reference 7

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Observation c3516cdb-cb7f-4efe-b026-c16c1d8198c7 · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

AI-Driven MRI-based Brain Tumour Segmentation Benchmarking SAM 2: Segment Anything in Images and Videos

Reference 8

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Observation 6009f4cc-25ed-4630-828a-3dd710f44266 · outbound

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

AI-Driven MRI-based Brain Tumour Segmentation Benchmarking SAM-Med3D: Towards General-purpose Segmentation Models for Volumetric Medical Images

Reference 9

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Observation 071b02e5-0e1a-4401-ad16-2920a9b283fa · outbound

This paper cites The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification.

AI-Driven MRI-based Brain Tumour Segmentation Benchmarking The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification

Reference 10

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Observation f5894b7c-2979-4f6d-a018-e4c066ed8498 · outbound

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

AI-Driven MRI-based Brain Tumour Segmentation Benchmarking Image Segmentation Using Deep Learning: A Survey,

Reference 11

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Observation 6623d7c9-190e-4221-a1fd-1893aaa84d11 · outbound

This paper cites Why rankings of biomedical image analysis competitions should be interpreted with care,.

AI-Driven MRI-based Brain Tumour Segmentation Benchmarking Why rankings of biomedical image analysis competitions should be interpreted with care,

Reference 12

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Observation 3c1062fa-f92b-45ad-b32e-78e24e648a68 · outbound

This paper cites DeepIGeoS: A Deep Interactive Geodesic Framework for Medical Image Segmentation,.

AI-Driven MRI-based Brain Tumour Segmentation Benchmarking DeepIGeoS: A Deep Interactive Geodesic Framework for Medical Image Segmentation,

Reference 13

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Observation 9a7780d2-5cad-455e-b555-636c3c54ee83 · outbound

This paper cites 3D U- net: Learning dense volumetric segmentation from sparse annotation,.

AI-Driven MRI-based Brain Tumour Segmentation Benchmarking 3D U- net: Learning dense volumetric segmentation from sparse annotation,

Reference 14

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Observation 6231ee3d-c5c9-478f-87a3-f960f16b23fc · outbound

This paper cites nnU-Net for Brain Tumor Segmentation,.

AI-Driven MRI-based Brain Tumour Segmentation Benchmarking nnU-Net for Brain Tumor Segmentation,

Reference 15

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Source-reported events for the cited work

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Observation edf84167-ff0d-41bb-a63b-b29167d7b99a · outbound

This paper cites Extending nn- UNet for Brain Tumor Segmentation,.

AI-Driven MRI-based Brain Tumour Segmentation Benchmarking Extending nn- UNet for Brain Tumor Segmentation,

Reference 16

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Observation 9365a1eb-845e-475c-8dbe-7e25dc8f208c · outbound

This paper cites Multimodal CNN Networks for Brain Tumor Segmentation in MRI: A BraTS 2022 Challenge Solution,.

AI-Driven MRI-based Brain Tumour Segmentation Benchmarking Multimodal CNN Networks for Brain Tumor Segmentation in MRI: A BraTS 2022 Challenge Solution,

Reference 17

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Observation cc244ad8-8e8e-4ecc-92bf-7cfcca24a964 · outbound

This paper cites How we won BraTS 2023 Adult Glioma challenge? Just faking it! Enhanced Synthetic Data Augmentation and Model Ensemble for brain tumour segmentation.

AI-Driven MRI-based Brain Tumour Segmentation Benchmarking How we won BraTS 2023 Adult Glioma challenge? Just faking it! Enhanced Synthetic Data Augmentation and Model Ensemble for brain tumour segmentation

Reference 18

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Observation 4677625f-6486-4437-bc22-bcaeb0b45824 · outbound

This paper cites Segment anything model for medical image analysis: An experimental study,.

AI-Driven MRI-based Brain Tumour Segmentation Benchmarking Segment anything model for medical image analysis: An experimental study,

Reference 19

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Observation 1199619f-7d92-4b6c-a0b9-39fb0e1d9125 · outbound

This paper cites Biomedical SAM 2: Segment Anything in Biomedical Images and Videos.

AI-Driven MRI-based Brain Tumour Segmentation Benchmarking Biomedical SAM 2: Segment Anything in Biomedical Images and Videos

Reference 20

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Observation ca34648f-23e9-4ba2-a497-d6454d8e7ea1 · outbound

This paper cites The SRI24 multichannel atlas of normal adult human brain structure,.

AI-Driven MRI-based Brain Tumour Segmentation Benchmarking The SRI24 multichannel atlas of normal adult human brain structure,

Reference 21

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Observation e1581123-2025-4c60-98d4-3027ba82e8f7 · outbound

This paper cites Data leakage inflates prediction performance in connectome- based machine learning models,.

AI-Driven MRI-based Brain Tumour Segmentation Benchmarking Data leakage inflates prediction performance in connectome- based machine learning models,

Reference 22

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Observation e5cc734b-a100-49a3-9c1e-4895638e83c3 · outbound

This paper cites The Brain Tumor Segmentation (BraTS) Challenge 2023: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs).

AI-Driven MRI-based Brain Tumour Segmentation Benchmarking The Brain Tumor Segmentation (BraTS) Challenge 2023: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs)

Reference 23

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Observation db12343b-09f3-4e41-9792-7bdd3a241700 · outbound

This paper cites Exploring the Impact of Dataset Statistical Effect Size on Model Performance and Data Sample Size Sufficiency.

AI-Driven MRI-based Brain Tumour Segmentation Benchmarking Exploring the Impact of Dataset Statistical Effect Size on Model Performance and Data Sample Size Sufficiency

Reference 24

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Observation 07a95e1b-d70c-460e-b046-df9697c5d9c9 · outbound

This paper cites Brain tumour segmentation with incomplete imaging data,.

AI-Driven MRI-based Brain Tumour Segmentation Benchmarking Brain tumour segmentation with incomplete imaging data,

Reference 25

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Observation b0b7d556-87c0-4827-98a4-11fa7da3202d · outbound

This paper cites Segment Anything in Medical Images and Videos: Benchmark and Deployment,.

AI-Driven MRI-based Brain Tumour Segmentation Benchmarking Segment Anything in Medical Images and Videos: Benchmark and Deployment,

Reference 26

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Pith citing papers

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