Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy | Paper Citation Record

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This paper cites The financial, operational, and clinical advantages of generalist radiology ai.Radiology, 316(3):e242362, 2025.

Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy The financial, operational, and clinical advantages of generalist radiology ai.Radiology, 316(3):e242362, 2025

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This paper cites Foundation models for generalist medical artificial intelligence.Nature, 616(7956):259–265, 2023.

Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Foundation models for generalist medical artificial intelligence.Nature, 616(7956):259–265, 2023

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This paper cites Medical image segmentation review: The success of u-net.IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(12):10076–10095, 2024.

Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Medical image segmentation review: The success of u-net.IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(12):10076–10095, 2024

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This paper cites A chain of diagnosis framework for accurate and explainable radiology report generation.IEEE Transactions on Medical Imaging, 2025.

Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy A chain of diagnosis framework for accurate and explainable radiology report generation.IEEE Transactions on Medical Imaging, 2025

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This paper cites A review of the application of deep learning in medical image classification and segmentation.Annals of translational medicine, 8(11):713, 2020.

Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy A review of the application of deep learning in medical image classification and segmentation.Annals of translational medicine, 8(11):713, 2020

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This paper cites Cotr: Efficiently bridging cnn and transformer for 3d medical image segmentation.

Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Cotr: Efficiently bridging cnn and transformer for 3d medical image segmentation

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This paper cites nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation.

Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation

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This paper cites End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography.

Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography

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This paper cites Large-scale pancreatic cancer detection via non-contrast ct and deep learning.Nature medicine, 29(12):3033–3043, 2023.

Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Large-scale pancreatic cancer detection via non-contrast ct and deep learning.Nature medicine, 29(12):3033–3043, 2023

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This paper cites Parse and recall: Towards accurate lung nodule ma- lignancy prediction like radiologists.

Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Parse and recall: Towards accurate lung nodule ma- lignancy prediction like radiologists

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This paper cites Towards a comprehensive, efficient and promptable anatomic structure segmentation model using 3d whole-body ct scans.

Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Towards a comprehensive, efficient and promptable anatomic structure segmentation model using 3d whole-body ct scans

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This paper cites Contrastive learning of medical visual representations from paired images and text.

Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Contrastive learning of medical visual representations from paired images and text

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

Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Making the most of text semantics to improve biomedical vision–language processing

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This paper cites Merlin: A vision language foundation model for 3d computed tomography.

Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Merlin: A vision language foundation model for 3d computed tomography

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This paper cites Umind-vl: A generalist ultrasound vision-language model for unified grounded perception and comprehensive interpretation.arXiv preprint arXiv:2511.22256, 2025.

Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Umind-vl: A generalist ultrasound vision-language model for unified grounded perception and comprehensive interpretation.arXiv preprint arXiv:2511.22256, 2025

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This paper cites Generalist versus Specialist Vision Foundation Models for Ocular Disease and Oculomics.

Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Generalist versus Specialist Vision Foundation Models for Ocular Disease and Oculomics

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This paper cites CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering.

Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering

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This paper cites GSCo: Towards Generalizable AI in Medicine via Generalist-Specialist Collaboration.

Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy GSCo: Towards Generalizable AI in Medicine via Generalist-Specialist Collaboration

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This paper cites Qwen Technical Report.

Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Qwen Technical Report

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This paper cites Large-scale and Fine-grained Vision-language Pre-training for Enhanced CT Image Understanding.

Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Large-scale and Fine-grained Vision-language Pre-training for Enhanced CT Image Understanding

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This paper cites A foundation model utilizing chest ct volumes and radiology reports for supervised-level zero-shot detection of abnormalities.arXiv preprint arXiv:2403.17834, 5, 2024.

Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy A foundation model utilizing chest ct volumes and radiology reports for supervised-level zero-shot detection of abnormalities.arXiv preprint arXiv:2403.17834, 5, 2024

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This paper cites Machine-learning-based multiple abnormality prediction with large-scale chest computed tomography volumes.Medical image analysis, 67:101857, 2021.

Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Machine-learning-based multiple abnormality prediction with large-scale chest computed tomography volumes.Medical image analysis, 67:101857, 2021

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This paper cites Towards Universal Text-driven CT Image Segmentation.

Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Towards Universal Text-driven CT Image Segmentation

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Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Hybrid cross-modality fusion network for medical image segmentation with contrastive learning.Engineering Applications of Artificial Intelligence, 144:110073, 2025

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This paper cites Vision-language semantic grounding for multi-domain crop-weed segmentation.arXiv preprint arXiv:2602.23677, 2026.

Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Vision-language semantic grounding for multi-domain crop-weed segmentation.arXiv preprint arXiv:2602.23677, 2026

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Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Learning transferable visual models from natural language supervision

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Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Joint learning of localized representations from medical images and reports

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Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Imitate: Clinical prior guided hierarchical vision-language pre-training.IEEE Transactions on Medical Imaging, 2024

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Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Bootstrapping chest ct image understanding by distilling knowledge from x-ray expert models

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Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Boosting vision semantic density with anatomy normality mod- eling for medical vision-language pre-training

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Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy A foundation model utilizing chest ct volumes and radiology reports for supervised-level zero-shot detection of abnormalities.CoRR, 2024

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Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Medclip-samv2: Towards universal text-driven medical image segmentation.Medical Image Analysis, page 103749, 2025

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Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy U-kan makes strong backbone for medical image segmentation and generation

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Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Semisam+: rethinking semi-supervised medical image segmentation in the era of foundation models.Medical Image Analysis, page 103733, 2025

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Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Medianomaly: A comparative study of anomaly detection in medical images.Medical Image Analysis, 102:103500, 2025

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Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Medical imaging: a critical review on x-ray imaging for the detection of infection.Biomedical Materials & Devices, 4(1):1–45, 2026

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Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Deep learning-based object detection algorithms in medical imaging: Systematic review.Heliyon, 11(1), 2025

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Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Resvit fusionnet model: An explainable ai-driven approach for automated grading of diabetic retinopathy in retinal images.Computers in Biology and Medicine, 186:109656, 2025

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Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Diffmic-v2: Medical image classification via improved diffusion network.IEEE Transactions on Medical Imaging, 44(5):2244–2255, 2025

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Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy A novel pd-1/pd-l1 pathway-related seven-gene signature for the development and validation of the prognosis prediction model for breast cancer

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Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Histo-genomic knowledge association for cancer prognosis from histopathology whole slide images.IEEE Transactions on Medical Imaging, 44(5):2170–2181, 2025

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Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy U-net: Convolutional networks for biomedical image segmentation

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Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy nnFormer: Interleaved Transformer for Volumetric Segmentation

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Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Swin unetr: Swin transformers for semantic segmentation of brain tumors in mri images

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Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy A visual–language foundation model for pathology image analysis using medical twitter.Nature medicine, 29(9):2307–2316, 2023

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Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Advancing Radiograph Representation Learning with Masked Record Modeling

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Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs

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Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Pmc-clip: Contrastive language-image pre-training using biomedical documents

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Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Expert-level detection of pathologies from unannotated chest x-ray images via self-supervised learning.Nature biomedical engineering, 6(12):1399–1406, 2022

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This paper cites Multi- granularity cross-modal alignment for generalized medical visual representation learning.Ad- vances in neural information processing systems, 35:33536–33549, 2022.

Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Multi- granularity cross-modal alignment for generalized medical visual representation learning.Ad- vances in neural information processing systems, 35:33536–33549, 2022

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This paper cites Towards generalizable ai in medicine via generalist-specialist collaboration.Nature Biomedical Engineering, 2026.

Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Towards generalizable ai in medicine via generalist-specialist collaboration.Nature Biomedical Engineering, 2026

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Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Bert: Pre-training of deep bidirectional transformers for language understanding

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Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Masked image modeling advances 3d medical image analysis

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Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy Localized Lesion

Reference 62

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