MedSG-Bench: A Benchmark for Medical Image Sequences Grounding | Paper Citation Record

Observation ab97bc87-02ce-4828-9ff6-97d5ced94ad8 · outbound

This paper cites https://tianchi.aliyun.com/dataset/83075, 2020.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding https://tianchi.aliyun.com/dataset/83075, 2020

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This paper cites GPT-4 Technical Report.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding GPT-4 Technical Report

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This paper cites Advance warning methodologies for covid-19 using chest x-ray images.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Advance warning methodologies for covid-19 using chest x-ray images

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This paper cites Dataset of breast ultrasound images.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Dataset of breast ultrasound images

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This paper cites 2017 Robotic Instrument Segmentation Challenge.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding 2017 Robotic Instrument Segmentation Challenge

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This paper cites The medical segmentation decathlon.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding The medical segmentation decathlon

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This paper cites Neural segmentation of seeding rois (srois) for pre-surgical brain tractography.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Neural segmentation of seeding rois (srois) for pre-surgical brain tractography

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Observation eb9d1763-3b1f-4758-aac6-fb781e7551b1 · outbound

This paper cites Qwen2.5-VL Technical Report.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Qwen2.5-VL Technical Report

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This paper cites Advancing the cancer genome atlas glioma mri collections with expert segmentation labels and radiomic features.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Advancing the cancer genome atlas glioma mri collections with expert segmentation labels and radiomic features

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This paper cites Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

Reference 10

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Observation 42602a3e-48de-4a4b-86c8-8c6a5b8d9f79 · outbound

This paper cites MAIRA-2: Grounded Radiology Report Generation.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding MAIRA-2: Grounded Radiology Report Generation

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Observation 9260a51e-23bf-4df8-a096-9a68d3978299 · outbound

This paper cites Wm-dova maps for accurate polyp highlighting in colonoscopy: Validation vs.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Wm-dova maps for accurate polyp highlighting in colonoscopy: Validation vs

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Observation 9116065e-cf1a-40de-87c7-0fbdf3b67c6a · outbound

This paper cites Comparative validation of polyp detection methods in video colonoscopy: results from the miccai 2015 endoscopic vision challenge.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Comparative validation of polyp detection methods in video colonoscopy: results from the miccai 2015 endoscopic vision challenge

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Observation de9a96bd-423c-4597-936b-223bbc7cd2c5 · outbound

This paper cites Deep learning techniques for automatic mri cardiac multi-structures segmentation and diagnosis: is the problem solved? IEEE transactions on medical imaging, 37(11):2514–2525, 2018.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Deep learning techniques for automatic mri cardiac multi-structures segmentation and diagnosis: is the problem solved? IEEE transactions on medical imaging, 37(11):2514–2525, 2018

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This paper cites an unresolved cited work.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Unresolved cited work

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Observation 4ec2cf37-4c53-4e8c-955d-80ed15b88a79 · outbound

This paper cites Making the most of text semantics to improve biomedical vision–language processing.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Making the most of text semantics to improve biomedical vision–language processing

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Observation 2efd32a0-b426-433d-bc23-4df83943f780 · outbound

This paper cites Padchest: A large chest x-ray image dataset with multi-label annotated reports.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Padchest: A large chest x-ray image dataset with multi-label annotated reports

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Observation dafee3bc-041c-4800-b0d5-a91d5fcc323c · outbound

This paper cites Lung segmentation in chest radiographs using anatomical atlases with nonrigid registration.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Lung segmentation in chest radiographs using anatomical atlases with nonrigid registration

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Observation eff77787-6e40-48e7-84ba-b2d2fe7f2b5b · outbound

This paper cites Longitudinal multiple sclerosis lesion segmentation: resource and challenge.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Longitudinal multiple sclerosis lesion segmentation: resource and challenge

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Observation 07975337-5dba-4b77-82b1-1f4658557184 · outbound

This paper cites HuatuoGPT-Vision, Towards Injecting Medical Visual Knowledge into Multimodal LLMs at Scale.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding HuatuoGPT-Vision, Towards Injecting Medical Visual Knowledge into Multimodal LLMs at Scale

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Observation fa90a5ff-a079-4bb9-b343-c584d42b2849 · outbound

This paper cites Shikra: Unleashing Multimodal LLM's Referential Dialogue Magic.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Shikra: Unleashing Multimodal LLM's Referential Dialogue Magic

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Observation 6f2e7d30-8d93-43b3-97f4-f589c51b8180 · outbound

This paper cites Towards generalizable tumor synthesis.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Towards generalizable tumor synthesis

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Observation a64f0afe-1f2c-43d2-b35d-3d6c54b9a5f7 · outbound

This paper cites Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

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Observation 0e15280a-6945-4be1-b4a1-0d1a81debdb5 · outbound

This paper cites How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites

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Observation 47ade6e0-84d5-47ac-ad66-45c167fa2913 · outbound

This paper cites Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks

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This paper cites Medical phrase grounding with region-phrase context contrastive alignment.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Medical phrase grounding with region-phrase context contrastive alignment

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Observation dd069e13-6f14-4c33-af5a-d830e1e9c799 · outbound

This paper cites Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC).

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)

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Observation bdb3b045-7f01-4180-a3c6-aa79831ef4ef · outbound

This paper cites COVID-19 Image Data Collection: Prospective Predictions Are the Future.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding COVID-19 Image Data Collection: Prospective Predictions Are the Future

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This paper cites Ctooth+: A large-scale dental cone beam computed tomography dataset and benchmark for tooth volume segmentation.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Ctooth+: A large-scale dental cone beam computed tomography dataset and benchmark for tooth volume segmentation

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Observation 58b3f9f6-28ed-4956-8842-56b1a1db0e5d · outbound

This paper cites Ctooth: a fully annotated 3d dataset and benchmark for tooth volume segmentation on cone beam computed tomography images.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Ctooth: a fully annotated 3d dataset and benchmark for tooth volume segmentation on cone beam computed tomography images

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Observation 3095f2f8-544b-4efd-92d0-6244637cfa7d · outbound

This paper cites Reliable covid-19 detection using chest x-ray images.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Reliable covid-19 detection using chest x-ray images

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This paper cites Covid-19 infection map generation and detection from chest x-ray images.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Covid-19 infection map generation and detection from chest x-ray images

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This paper cites Osegnet: Operational segmentation network for covid-19 detection using chest x-ray images.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Osegnet: Operational segmentation network for covid-19 detection using chest x-ray images

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This paper cites CTSpine1K: A Large-Scale Dataset for Spinal Vertebrae Segmentation in Computed Tomography.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding CTSpine1K: A Large-Scale Dataset for Spinal Vertebrae Segmentation in Computed Tomography

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This paper cites Automatic atlas-based segmentation of the prostate: A miccai 2009 prostate segmentation challenge entry.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Automatic atlas-based segmentation of the prostate: A miccai 2009 prostate segmentation challenge entry

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This paper cites Joint optic disc and cup segmentation based on multi-label deep network and polar transformation.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Joint optic disc and cup segmentation based on multi-label deep network and polar transformation

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Observation ed0f7312-72e7-44b4-a43b-038eb29072e0 · outbound

This paper cites Palm: Pathologic myopia challenge.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Palm: Pathologic myopia challenge

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Observation 5c6f03fb-b103-4867-99e5-3e77e0683482 · outbound

This paper cites Age challenge: angle closure glaucoma evaluation in anterior segment optical coherence tomography.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Age challenge: angle closure glaucoma evaluation in anterior segment optical coherence tomography

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This paper cites Rim-one: An open retinal image database for optic nerve evaluation.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Rim-one: An open retinal image database for optic nerve evaluation

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This paper cites Bayeseg: Bayesian modeling for medical image segmentation with interpretable generalizability.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Bayeseg: Bayesian modeling for medical image segmentation with interpretable generalizability

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This paper cites Thyroid nodule segmentation and classification in ultrasound images.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Thyroid nodule segmentation and classification in ultrasound images

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This paper cites Bagls, a multihospital benchmark for automatic glottis segmentation.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Bagls, a multihospital benchmark for automatic glottis segmentation

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Observation f75b5507-8b95-46c6-a5d6-d94858ee063e · outbound

This paper cites Computer Aided Detection for Pulmonary Embolism Challenge (CAD-PE).

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Computer Aided Detection for Pulmonary Embolism Challenge (CAD-PE)

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This paper cites Segmentation of knee images: a grand challenge.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Segmentation of knee images: a grand challenge

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This paper cites Isles 2022: A multi-center magnetic resonance imaging stroke lesion segmentation dataset.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Isles 2022: A multi-center magnetic resonance imaging stroke lesion segmentation dataset

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This paper cites The endotect 2020 challenge: evaluation and comparison of classification, segmentation and inference time for endoscopy.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding The endotect 2020 challenge: evaluation and comparison of classification, segmentation and inference time for endoscopy

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Observation 9c9ed533-4fad-4938-9657-1742b2ffd6b9 · outbound

This paper cites Computed tomography images for intracranial hemorrhage detection and segmentation.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Computed tomography images for intracranial hemorrhage detection and segmentation

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Observation ca10e1e2-7076-4190-8e41-1c3656628c62 · outbound

This paper cites Label-free liver tumor segmentation.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Label-free liver tumor segmentation

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Observation db46861d-7482-491e-9b0b-0c83f0c1723b · outbound

This paper cites Domain specific convolution and high frequency reconstruction based unsupervised domain adaptation for medical image segmentation.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Domain specific convolution and high frequency reconstruction based unsupervised domain adaptation for medical image segmentation

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Observation bfc46347-dac8-452c-bbd9-88d1107f56b0 · outbound

This paper cites Medical-diff-vqa: a large-scale medical dataset for difference visual question answering on chest x-ray images.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Medical-diff-vqa: a large-scale medical dataset for difference visual question answering on chest x-ray images

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Observation 8dbfe148-8659-47c1-928f-7725a69ac0c0 · outbound

This paper cites Om- nimedvqa: A new large-scale comprehensive evaluation benchmark for medical lvlm.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Om- nimedvqa: A new large-scale comprehensive evaluation benchmark for medical lvlm

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Observation 58fb7fc0-402b-49ad-b8b1-f59161ddf8f2 · outbound

This paper cites Towards a multimodal large language model with pixel-level insight for biomedicine.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Towards a multimodal large language model with pixel-level insight for biomedicine

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Observation f7e5b85d-eb09-407c-a0cf-fde8cfc90648 · outbound

This paper cites Automatic tuberculosis screening using chest radiographs.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Automatic tuberculosis screening using chest radiographs

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This paper cites Hugging face.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Hugging face

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Observation 8d9fed1c-0ef6-41cb-bfda-c38d661f860f · outbound

This paper cites Kvasir-instrument: Diagnostic and therapeutic tool segmentation dataset in gastrointestinal endoscopy.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Kvasir-instrument: Diagnostic and therapeutic tool segmentation dataset in gastrointestinal endoscopy

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

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Amos: A large-scale abdominal multi-organ bench- mark for versatile medical image segmentation

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Observation 84ef0500-d2f5-4e98-9a62-995067928e60 · outbound

This paper cites MANTIS: Interleaved Multi-Image Instruction Tuning.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding MANTIS: Interleaved Multi-Image Instruction Tuning

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Observation 66437ede-5786-4b06-80fd-7bf12bb9742e · outbound

This paper cites ChatRex: Taming Multimodal LLM for Joint Perception and Understanding.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding ChatRex: Taming Multimodal LLM for Joint Perception and Understanding

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Observation 3690c6a1-a75c-4e30-9d8a-3ecc19b19529 · outbound

This paper cites an unresolved cited work.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Unresolved cited work

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-15T20:50:47.710238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4af9e8fe-38e8-4944-8977-83a969eadc01 · outbound

This paper cites Xr-msf-unet: Automatic segmentation model for covid-19 lung ct images.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Xr-msf-unet: Automatic segmentation model for covid-19 lung ct images

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-15T20:50:47.716320Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 851a2042-7305-4b6f-92d9-fff84d2de631 · outbound

This paper cites Covid-19 ct lung and infection segmentation dataset.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Covid-19 ct lung and infection segmentation dataset

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-15T20:50:47.721870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74379ad2-6b5b-4be8-afee-9fb42896c77b · outbound

This paper cites Algorithms for left atrial wall segmentation and thickness–evaluation on an open-source ct and mri image database.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Algorithms for left atrial wall segmentation and thickness–evaluation on an open-source ct and mri image database

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-15T20:50:47.726813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ffd5496d-74fc-456d-8aa1-953d0d4fc58d · outbound

This paper cites Segment anything.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Segment anything

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-15T20:50:47.732587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be4495f9-74a4-439c-888c-3054e31a8bd0 · outbound

This paper cites Visual genome: Connecting language and vision using crowdsourced dense image annotations.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Visual genome: Connecting language and vision using crowdsourced dense image annotations

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-15T20:50:47.737626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 60dacd3a-c2e0-40f5-a548-114f0ec31872 · outbound

This paper cites Standardized assessment of automatic segmentation of white matter hyperintensities and results of the wmh segmentation challenge.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Standardized assessment of automatic segmentation of white matter hyperintensities and results of the wmh segmentation challenge

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-15T20:50:47.742377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0990dff-0f09-48c7-b399-2bb01818760b · outbound

This paper cites Lisa: Reasoning segmentation via large language model.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Lisa: Reasoning segmentation via large language model

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-15T20:50:47.747954Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3586df5e-d23b-4a66-af3a-0b5b3b0c825d · outbound

This paper cites Deep learning methods for automatic evaluation of delayed enhancement-mri.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Deep learning methods for automatic evaluation of delayed enhancement-mri

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-15T20:50:47.752897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b4013f7b-da50-49df-a37e-9641f80ce4f1 · outbound

This paper cites Segthor: Segmentation of thoracic organs at risk in ct images.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Segthor: Segmentation of thoracic organs at risk in ct images

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-15T20:50:47.757611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17cff991-05d0-4936-adbb-00fb4279502e · outbound

This paper cites A dataset of clinically generated visual questions and answers about radiology images.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding A dataset of clinically generated visual questions and answers about radiology images

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-15T20:50:47.762221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2202b2c0-1f15-4cad-978c-b36f886bc2f2 · outbound

This paper cites Deep learning for segmentation using an open large-scale dataset in 2d echocardiography.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Deep learning for segmentation using an open large-scale dataset in 2d echocardiography

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-15T20:50:47.766743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59cdfa1f-cd76-4158-876d-e3b6df8f51e7 · outbound

This paper cites Computer-aided detection and diagnosis for prostate cancer based on mono and multi-parametric mri: a review.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Computer-aided detection and diagnosis for prostate cancer based on mono and multi-parametric mri: a review

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-15T20:50:47.771538Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 75754d60-050a-4837-a53d-af67fb802632 · outbound

This paper cites LLaVA-OneVision: Easy Visual Task Transfer.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding LLaVA-OneVision: Easy Visual Task Transfer

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-15T20:50:47.776608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93067a81-d127-43c2-aa07-6c4045474c1a · outbound

This paper cites Cutpaste: Self-supervised learning for anomaly detection and localization.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Cutpaste: Self-supervised learning for anomaly detection and localization

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-15T20:50:47.781489Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e9666b0a-f478-4f02-bbbd-15a7d4191867 · outbound

This paper cites Development and clinical deployment of a smartphone- based visual field deep learning system for glaucoma detection.NPJ digital medicine, 3(1):123, 2020.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Development and clinical deployment of a smartphone- based visual field deep learning system for glaucoma detection.NPJ digital medicine, 3(1):123, 2020

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-15T20:50:47.787378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85940ae1-7c10-4900-9fc5-0b8405ec1650 · outbound

This paper cites QUBIQ: Uncertainty Quantification for Biomedical Image Segmentation Challenge.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding QUBIQ: Uncertainty Quantification for Biomedical Image Segmentation Challenge

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-15T20:50:47.792874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e2bd617-6add-4512-9c5b-747f4cd2aae7 · outbound

This paper cites The state-of-the-art 3D anisotropic intracranial hemorrhage segmentation on non-contrast head CT: The INSTANCE challenge.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding The state-of-the-art 3D anisotropic intracranial hemorrhage segmentation on non-contrast head CT: The INSTANCE challenge

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-15T20:50:47.798115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c8f7659-58fc-41c6-88d5-df68a6583a27 · outbound

This paper cites Hematoma expansion context guided intracranial hemorrhage segmentation and uncertainty estimation.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Hematoma expansion context guided intracranial hemorrhage segmentation and uncertainty estimation

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:50:49.768028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e55e4bdb-d8b0-437a-9897-698b0016b6da · outbound

This paper cites Migician: Revealing the Magic of Free-Form Multi-Image Grounding in Multimodal Large Language Models.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Migician: Revealing the Magic of Free-Form Multi-Image Grounding in Multimodal Large Language Models

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-15T20:50:47.809142Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87b9f929-3492-4382-9ada-87f94501cc62 · outbound

This paper cites Evaluation of prostate segmentation algorithms for mri: the promise12 challenge.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Evaluation of prostate segmentation algorithms for mri: the promise12 challenge

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:50:49.749585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 01d9a2c3-985b-4ec3-b1f8-b25b4c756076 · outbound

This paper cites Slake: A semantically- labeled knowledge-enhanced dataset for medical visual question answering.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Slake: A semantically- labeled knowledge-enhanced dataset for medical visual question answering

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:50:49.729836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8c900e84-c22d-488b-8532-5c3acb74575d · outbound

This paper cites Deep learning to segment pelvic bones: large-scale ct datasets and baseline models.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Deep learning to segment pelvic bones: large-scale ct datasets and baseline models

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:50:49.710628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 903ca41b-3cac-4554-81ed-2a4c3cfad846 · outbound

This paper cites Grounding dino: Marrying dino with grounded pre-training for open-set object detection.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Grounding dino: Marrying dino with grounded pre-training for open-set object detection

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:50:49.689944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 132ec49e-21e5-4fc8-9c41-0839ecae6dc8 · outbound

This paper cites A vertebral segmentation dataset with fracture grading.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding A vertebral segmentation dataset with fracture grading

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:50:49.670754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ec454d2c-5f4b-4e14-9938-998b21f83c03 · outbound

This paper cites Efficient automatic segmentation for multi-level pulmonary arteries: The PARSE challenge.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Efficient automatic segmentation for multi-level pulmonary arteries: The PARSE challenge

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-15T20:50:47.837186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9aa08f1-c643-4fa8-9f4d-e575e1144c5d · outbound

This paper cites Segrap2023: A benchmark of organs-at-risk and gross tumor volume segmentation for radiotherapy planning of nasopharyn- geal carcinoma.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Segrap2023: A benchmark of organs-at-risk and gross tumor volume segmentation for radiotherapy planning of nasopharyn- geal carcinoma

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:50:49.653584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0c733819-a03e-46ab-ac5d-936be3220cdc · outbound

This paper cites Word: A large scale dataset, benchmark and clinical applicable study for abdominal organ segmentation from ct image.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Word: A large scale dataset, benchmark and clinical applicable study for abdominal organ segmentation from ct image

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:50:49.635709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a4afc78e-9a4a-476c-b575-d80d07c1efa0 · outbound

This paper cites X-metric: An n-dimensional information-theoretic framework for groupwise registration and deep combined computing.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding X-metric: An n-dimensional information-theoretic framework for groupwise registration and deep combined computing

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:50:49.618071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 148a4eb2-94f8-46b5-96d8-c14cd262357f · outbound

This paper cites Groma: Localized visual tokenization for grounding multimodal large language models.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Groma: Localized visual tokenization for grounding multimodal large language models

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:50:49.601494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation caff4e62-6c50-4061-8217-d90147265ec8 · outbound

This paper cites Segment anything in medical images.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Segment anything in medical images

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-15T20:50:47.861237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1736e26e-ddd1-4b80-b7e3-a21e5ad35e0e · outbound

This paper cites Abdomenct-1k: Is abdominal organ segmentation a solved problem? IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(10):6695– 6714, 2021.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Abdomenct-1k: Is abdominal organ segmentation a solved problem? IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(10):6695– 6714, 2021

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:50:49.572846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8a9dafe5-9eed-442e-a346-4280bc104cb0 · outbound

This paper cites The multimodal brain tumor image segmentation benchmark (brats).

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding The multimodal brain tumor image segmentation benchmark (brats)

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-15T20:50:47.871673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7971358a-1adc-4be4-b32a-7ad6a0219500 · outbound

This paper cites MMXU: A Multi-Modal and Multi-X-ray Understanding Dataset for Disease Progression.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding MMXU: A Multi-Modal and Multi-X-ray Understanding Dataset for Disease Progression

Reference 92

Resolution: verified exact; local_arxiv, observed 2026-08-15T20:50:48.530706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c2cd59e5-3d29-42d5-a45f-168a5e331ab2 · outbound

This paper cites Automatic segmentation of white matter tracts using multiple brain mri sequences.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Automatic segmentation of white matter tracts using multiple brain mri sequences

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:50:49.542601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 76803f2e-c628-458b-b600-7ea352929d1d · outbound

This paper cites Vindr-mammo: A large-scale benchmark dataset for computer-aided diagnosis in full-field digital mammography.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Vindr-mammo: A large-scale benchmark dataset for computer-aided diagnosis in full-field digital mammography

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:50:49.522724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation aca00442-1d86-4d06-bfbf-87af2c4813f8 · outbound

This paper cites Brain tumor mri dataset.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Brain tumor mri dataset

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:50:49.498476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 31a19695-e9d5-446d-9982-93e692de0a60 · outbound

This paper cites chatgpto3.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding chatgpto3

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:50:49.479425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1dfb4d6e-a881-4fae-84fe-5ae56882fdfa · outbound

This paper cites Refuge challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Refuge challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:50:49.461759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation cd46d04b-60bc-493e-95df-64f259d1a21f · outbound

This paper cites Interactive whole-heart segmentation in congenital heart disease.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Interactive whole-heart segmentation in congenital heart disease

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:50:49.441439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2de82729-568c-4f22-be5b-3ba6f2156524 · outbound

This paper cites Dgmsnet: Spine segmentation for mr image by a detection-guided mixed-supervised segmentation network.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Dgmsnet: Spine segmentation for mr image by a detection-guided mixed-supervised segmentation network

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:50:49.422180Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7597b807-6743-44b1-b532-aaf83b01fd0d · outbound

This paper cites Spineparsenet: spine parsing for volumetric mr image by a two-stage segmentation framework with semantic image representation.

MedSG-Bench: A Benchmark for Medical Image Sequences Grounding Spineparsenet: spine parsing for volumetric mr image by a two-stage segmentation framework with semantic image representation

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-15T20:50:47.916511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Reference resolution

Outbound references

Pith citing papers