GLoRIA: A Multimodal Global-Local Representation Learning Framework for Label-efficient Medical Image Recognition

Deep Residual Learning for Image Recognition

He, K., Zhang, X., Ren, S., & Sun, J. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.90 · Cited by 235,474

U-Net: Convolutional Networks for Biomedical Image Segmentation

Ronneberger, O., Fischer, P., & Brox, T. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-24574-4_28 · Cited by 99,404

Learning Transferable Visual Models From Natural Language Supervision

Radford, A., Kim, J. W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al. (2021) · arXiv · doi:10.48550/arxiv.2103.00020 · Cited by 15,293

Show, Attend and Tell: Neural Image Caption Generation with Visual Attention

Xu, K., Ba, J., Kiros, R., Cho, K., Courville, A., Salakhutdinov, R., Zemel, R., & Bengio, Y. (2015) · arXiv · doi:10.48550/arxiv.1502.03044 · Cited by 8,248

MIMIC-III, a freely accessible critical care database

Johnson, A. E. W., Pollard, T. J., Shen, L., Lehman, L.-W. H., Feng, M., Ghassemi, M., Moody, B., Szolovits, P., Anthony Celi, L., & Mark, R. G. (2016) · Scientific Data · doi:10.1038/sdata.2016.35 · Cited by 8,141

Deep visual-semantic alignments for generating image descriptions

Karpathy, A., & Fei-Fei, L. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298932 · Cited by 4,902

ChestX-Ray8: Hospital-Scale Chest X-Ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases

Wang, X., Peng, Y., Lu, L., Lu, Z., Bagheri, M., & Summers, R. M. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.369 · Cited by 4,616

VQA: Visual Question Answering

Antol, S., Agrawal, A., Lu, J., Mitchell, M., Batra, D., Zitnick, C. L., & Parikh, D. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.279 · Cited by 4,487

AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks

Xu, T., Zhang, P., Huang, Q., Zhang, H., Gan, Z., Huang, X., & He, X. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00143 · Cited by 1,923

Learning to detect unseen object classes by between-class attribute transfer

Lampert, C. H., Nickisch, H., & Harmeling, S. (2009) · 2009 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2009.5206594 · Cited by 1,849

MHG-Adapter: A parameter-efficient multimodal hypergraph adapter for text-driven medical image segmentation

Mo, S., Cai, M. J., Lin, L., Tong, R., Wang, F., Chen, Q., Li, Y., Hu, H., & Chen, Y. (2025) · Displays · doi:10.1016/j.displa.2025.103330 · Cited by 1

Wholistic report generation for Breast ultrasound using LangChain

Huh, J., Ahn, H. S., Park, H. J., & YE, J. C. (2025) · Computerized Medical Imaging and Graphics · doi:10.1016/j.compmedimag.2025.102697 · Cited by 1

MedCMCL-VLP: A Cross-Modal Dual-Phase Progressive Curriculum Learning Vision-Language Pre-Training Framework for Radiology Zero-Shot Classification

Li, J., Li, Z., Chi, J., & Bi, Z. (2025) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm66473.2025.11356033 · Cited by 1

HF-VLP: A multimodal vision-language pre-trained model for diagnosing heart failure

Ma, H., Li, D., Zhao, G., Liu, L., Fu, J., Fan, X., Zhang, Z., & Liang, Y. (2026) · Computerized Medical Imaging and Graphics · doi:10.1016/j.compmedimag.2026.102719 · Cited by 1

FCUFormer: A multi-view informed vision-language foundation model for interpreting fetal cardiac ultrasound abnormalities

Chen, B., Zhao, Y., Du, C., Liu, X., & Chen, X. (2026) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2026.110225 · Cited by 1

Language-Guided Segmentation of Medical Images: A Review of Foundation Models

Qamar, S. (2026) · Bioengineering · doi:10.3390/bioengineering13070803 · Cited by 1

When multi-institutional dataset aggregation masks shortcut-like behavior in Foundation Models for medical imaging

Germani, É., Zeineddine, F., Mourad, C. J., & Albarqouni, S. (2026) · Medical Image Analysis · doi:10.1016/j.media.2026.104258 · Cited by 2

Exploring Vision Language Pretraining with Knowledge Enhancement via Large Language Model

Tung, C., Lin, Y., Yin, J., Ye, Q., & Chen, H. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-67751-9_7 · Cited by 1

Anatomy-guided slice-description interaction for multimodal brain disease diagnosis based on 3D image and radiological report

Gao, X., Zhang, M., Li, J., Zhao, S., Zhuo, Z., Qu, L., Weng, J., Chai, L., Duan, Y., Ye, C., et al. (2025) · Computerized Medical Imaging and Graphics · doi:10.1016/j.compmedimag.2025.102556 · Cited by 1

Anatomical Grounding Pre-Training for Medical Phrase Grounding

Zhang, W., Chandra, S. S., & Nicolson, A. (2025) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi60581.2025.10980652 · Cited by 1

Cross-modal associated learning with spatial–temporal attention for hot topic detection

Zhang, C., Liu, S., Li, X., & Xiao, X. (2025) · Knowledge and Information Systems · doi:10.1007/s10115-025-02444-z · Cited by 1

VICCA: Visual interpretation and comprehension of chest X-ray anomalies in generated report without human feedback

Picha, S. G., Chanti, D. A., & Caplier, A. (2025) · Machine Learning with Applications · doi:10.1016/j.mlwa.2025.100684 · Cited by 1

AdFair-CLIP: Adversarial Fair Contrastive Language-Image Pre-training for Chest X-Rays

Yi, C., Xiong, Z., Qi, Q., Wei, X., Bathla, G., Lin, C., Mortazavi, B. J., & Yang, T. (2025) · Lecture notes in computer science · doi:10.1007/978-3-032-04978-0_2 · Cited by 1

SimCroP: Radiograph Representation Learning with Similarity-Driven Cross-Granularity Pre-training

Wang, R., Tang, F., Yao, Q., Yan, R., Zhang, X., Huang, Z., Lai, H., He, Z., Tao, X., Jiang, Z., et al. (2025) · Lecture notes in computer science · doi:10.1007/978-3-032-04971-1_53 · Cited by 1

Medical Contrastive Learning of Positive and Negative Mentions

Wu, W., Yang, J., Zhu, X., Zhang, X., Liu, Z., Li, M., & Wu, J. Y. (2025) · Lecture notes in computer science · doi:10.1007/978-3-032-05141-7_38 · Cited by 1

OFF-CLIP: Improving Normal Detection Confidence in Radiology CLIP with Simple Off-Diagonal Term Auto-adjustment

Park, J., Moon, C., Lee, D., Kim, K., & Hwang, M. (2025) · Lecture notes in computer science · doi:10.1007/978-3-032-04981-0_36 · Cited by 1

Adapting Vision Language Models for Structured Clinical Description Generation in Mammography

Castro, A. C., Rodrigues, D., & Filho, A. R. G. (2025) · Lecture notes in computer science · doi:10.1007/978-3-032-05559-0_24 · Cited by 1

Multimodal Artwork Topic Modeling via Fine-Tuned Clip and Knowledge-Driven Prompts

Scaringi, R., Stea, G., Fanelli, N., Vessio, G., & Castellano, G. (2025) · Machine learning for signal processing ... · doi:10.1109/mlsp62443.2025.11204345 · Cited by 1

Multi-Level CLS Token Fusion for Contrastive Learning in Endoscopy Image Classification

Nguyen, Y.-H., Huu, D. A. P., Tran, T. T., Nam, N., Giap, V. T., Dao, T. T. P., & Le, T.-N. (2025) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3746027.3762093 · Cited by 1

REMEMBER: Retrieval-based Explainable Multimodal Evidence-guided Modeling for Brain Evaluation and Reasoning in Zero- and Few-shot Neurodegenerative Diagnosis

Can, D.-C., Tang, Q.-H., Ha, H., Nguyen, B. T., & Chén, O. Y. (2025) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3746027.3754809 · Cited by 1

AdaHet-MKD: An Adaptive Heterogeneous Multi-teacher Knowledge Distillation for Medical Image Analysis

Wang, H., Du, W., Liu, N., Li, Q., Xu, Y., & Cui, L. (2025) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3746252.3761176 · Cited by 1

Ontology-regularized hierarchical transformers for anatomy and phenotype-aware medical image retrieval

Yan, T. (2025) · Journal of King Saud University - Computer and Information Sciences · doi:10.1007/s44443-025-00372-0 · Cited by 1

Comprehensive Comparative Analysis of State-of-the-Art Medical Vision-Language Models: LLaVA-Med, VILA-M3, and BiomedCLIP Performance Evaluation on Chest Radiography Datasets

Tarik, L., & Radouane, M. (2025) · International Conference on Intelligent Systems: Theories and Applications · doi:10.1109/sita67914.2025.11273425 · Cited by 1

Enhanced Prediction of Intracranial Aneurysm Rupture Risk via Multimodal Fusion

Zhang, X., Li, Q., Shao, J., Guo, W., Li, X., Liu, X., Li, H., & Jia, M. (2025) · IET Image Processing · doi:10.1049/ipr2.70260 · Cited by 1

Visualizing Radiologic Connections: An Explainable Coarse-to-Fine Foundation Model with Multiview Mammograms and Associated Reports

Gao, Y., Zhou, H.-Y., Wang, X., Portaluri, A., Zhang, T., Beets‐Tan, R. G. H., Han, L., Lu, C., Estacio, L., D'Angelo, A. R., et al. (2025) · Radiology Artificial Intelligence · doi:10.1148/ryai.240646 · Cited by 1

Chest X-ray foundation models: A survey and future directions

Wang, A., Yang, Z., Rais-Bahrami, S., & Yan, P. (2025) · Meta-Radiology · doi:10.1016/j.metrad.2025.100203 · Cited by 1

Contrastive Learning with Feature Space Interpolation for Retrieval-Based Chest X-Ray Report Generation

Rahman, Z. U., Yu, G.-H., Lee, J., & Kim, J.-Y. (2026) · Applied Sciences · doi:10.3390/app16010470 · Cited by 1

Spatial-Aware Symmetric Alignment for Text-Guided Medical Image Segmentation

Liao, L., Liu, Y., & Geng, Q. (2025) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm66473.2025.11356065 · Cited by 1

ModAn-MulSupCon: Modality- and anatomy-aware multi-label supervised contrastive pretraining for medical imaging

Takaya, E., & Inamori, R. (2026) · Computer Methods and Programs in Biomedicine Update · doi:10.1016/j.cmpbup.2026.100246 · Cited by 1

brat : Aligned Multi-View Embeddings for Brain MRI Analysis

Kayser, M., Gridnev, M., Wang, W., Bain, M., Rangnekar, A., Chatterjee, A., Petrov, A., Veeraraghavan, H., & Swinburne, N. (2026) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv61042.2026.00568 · Cited by 1

Uncertainty-Aware Vision-Language Segmentation for Medical Imaging

Das, A., Rachamalla, T., Biswas, K., Roy, S. K., & Verma, V. K. (2026) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv61042.2026.00819 · Cited by 1

A multimodal deep learning framework for clinical nursing assessment in lumbar fusion surgery via representation learning and feature extraction

Li, C., Cai, J., Huang, X., Ni, Y., Ling, X., & Fang, S. (2026) · Scientific Reports · doi:10.1038/s41598-026-51495-x · Cited by 1

PatchCLIP enables region specific contrastive health record and image joint training with patch embedding loss

Bhat, S., Mansoor, A., Georgescu, B., Zinnen, M., Sahu, P., Panambur, A. B., Ghesu, F. C., Grbić, S., & Maier, A. (2026) · Scientific Reports · doi:10.1038/s41598-026-52235-x · Cited by 1

CausalCompNet: Causal intervention meets vision-language priors for robust CXR diagnosis

Liu, M., Li, Q., Chang, R., Xu, Z., Zhou, C., & Nie, W. (2026) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2026.110554 · Cited by 1

A Comprehensive Review of Artificial Intelligence for Brain Tumor Analysis: Taxonomy, Robustness, and Open Challenges in Neuro-Oncology

Qasem, M. H., Sariera, T. M. A., Alhumaid, K. F., Alshraah, S. M., Mufleh, A. S. S., & Chihaoui, N. (2026) · Journal of Imaging · doi:10.3390/jimaging12060228 · Cited by 1

CheXmix: Unified Generative Pretraining for Vision Language Models in Medical Imaging

Kumar, A., Holland, R., Barrett, C., Kim, J., Varma, M., Chen, Z., Gao, Y., Zaharchuk, G., Taghavi, T., Kenthapadi, K., et al. (2026) · doi:10.1109/cvprf71909.2026.00907 · Cited by 1

MeFormer: Generating Radiology Reports via Memory Enhanced Pretraining Transformer

Li, F., Wang, P., Lin, K., & Wang, J. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-35415-1_6 · Cited by 1

Identification of difficult laryngoscopy using an optimized hybrid architecture

Liu, X., Flanagan, C., Li, G., Lei, Y., Zeng, L., Fang, J., Guo, X., McGrath, S., & Han, Y. (2024) · BMC Medical Research Methodology · doi:10.1186/s12874-023-02115-z · Cited by 1

Attention-Enhanced Guided Multimodal and Semi-Supervised Networks for Visual Acuity (VA) Prediction after Anti-VEGF Therapy

Wang, Y., Wang, Y., Liu, X., Cui, W., Jin, P., Cheng, Y., & Jia, G. (2024) · Electronics · doi:10.3390/electronics13183701 · Cited by 1

Bootstrapping Radiography Pre-training via Siamese Masked Vision-Language Modeling with Complementary Self-distillation

Li, W., Luo, L., & Chen, H. (2024) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm62325.2024.10822757 · Cited by 1

Medical Transformer With Mix Mask Generation for Thorax Disease Classification

Liu, Z., Wang, Z., & Du, B. (2025) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2025.3543003 · Cited by 1

Multimodal Representation Learning for Blastocyst Assessment

Wang, Y., Zheng, Z., Ni, N., Tong, G., Cheng, N., Li, K., Yin, P., Chen, Y., Wu, Y., & Xie, G. (2023) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi53787.2023.10230468 · Cited by 1

That’s the Wrong Lung! Evaluating and Improving the Interpretability of Unsupervised Multimodal Encoders for Medical Data

McInerney, D. J., Young, G., van de Meent, J.-W., & Wallace, B. (2022) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2022.emnlp-main.238 · Cited by 1

Deep Learning-Based Noninvasive Auxiliary Pulmonary TumorDiagnosis System on Multi-modality Radio-mics DataPreprint

Jiang, H. J. H., Chao, L. C. L., Chen, W. C. W., Zhang, J. Z. J., & Tai, Y. T. Y. (2023) · Research Square · doi:10.21203/rs.3.rs-3174078/v1

An interface for clinicians: finding crucial information with language models in electronic health records

McInerney, D. J. (2024) · Digital Repository Service (Northeastern University) · doi:10.17760/d20653001

Automated Brain Abnormality Detection using a Self-Supervised Text-Vision FrameworkPreprint

Wood, D. A., Guilhem, E., Kafiabadi, S., Busaidi, A. A., Hammam, A., Mansoor, N. M., Townend, M., Agarwal, S., Wei, Y., Mazumder, A., et al. (2024) · doi:10.22541/au.171571444.45086524/v2

A self-supervised framework for abnormality detection from brain MRIPreprint

Wood, D. A., Guilhem, E., Kafiabadi, S., Busaidi, A. A., Dissanayake, K., Hammam, A., Mansoor, N. M., Townend, M., Agarwal, S., Wei, Y., et al. (2024) · doi:10.22541/au.171900128.89392883/v1

Multimodal Local Representation Learning for Multi-Task Blastocyst Assessment

Zhang, J., Zheng, B., Ni, N., Tong, G., Wu, Y., Xie, G., & Yang, R. (2024) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi56570.2024.10635863

Two-Stage Medical Image-Text Transfer with Supervised Contrastive Learning

Wang, X., Yin, S., Wang, Y., Li, J., & Li, S. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-72353-7_32

Learning from Inside: Self-driven Intra-modality Siamese Knowledge Generation and Inter-modality Alignment for Chest X-rays Vision-Language Pre-training

Qiao, L., Cheng, L. D., Shu, Y., Luan, X., & Xiao, B. (2024) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm62325.2024.10822282

Improving CLIP for Biomedical Retrieval: A Multi-Margin Contrastive Loss Approach

Shakya, E., Rayakota, H. P., & Huang, P.-C. (2024) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata62323.2024.10825400

GILED: Lesion Detection of Gastrointestinal Tract from Endoscopic Images and Medical Notes

Hoang, V.-A., Tran, M.-H., Dao, H. V., & Tran, T.-H. (2024) · Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) · doi:10.1109/apsipaasc63619.2025.10849140

Bilateral network with text guided aggregation architecture for lung infection image segmentation

Pan, X., Mei, H., Zheng, J., & Zheng, H. (2025) · Biomedical Physics & Engineering Express · doi:10.1088/2057-1976/adb290

Multi-Modality Knowledge Transfer for Generalizable Chest Radiograph Interpretation

Hou, X., Li, Y., Mei, Y., Liu, D., & Wang, S. (2024) · International Conference on Biomedical and Bioinformatics Engineering (ICBBE) · doi:10.1145/3707127.3707128

Deep Learning-based Image Recognition Technology in Medical Diagnosis

Wu, X. (2025) · Applied Mathematics and Nonlinear Sciences · doi:10.2478/amns-2025-0008

Conjugate Cross-Modal Attention UNet for Medical Image Segmentation

Yuming, C., & He, L. (2024) · International Conference on Systems and Informatics (ICSAI) · doi:10.1109/icsai65059.2024.10893737

MedMM: A Multimodal Fusion Framework for 3D Medical Image Classification with Multigranular Text Guidance

Zhao, S., Zhang, M., Zhu, X., Li, J., Duan, Y., Zhuo, Z., Liu, Y., & Ye, C. (2024) · International Conference on Big Data Computing and Communications (BigCom) · doi:10.1109/bigcom65357.2024.00015

A Comparison of Object Detection and Phrase Grounding Models in Chest X-Ray Abnormality Localization Using Eye-Tracking Data

Ghelichkhan, E., & Taşdizen, T. (2025) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi60581.2025.10981290

TA-MIR: Text Aggregation for Multimodal Feature Representation in Medical Image Registration

Dai, Y., Huang, Z., & Huang, W. (2025) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi60581.2025.10981063

Effective Medical Visual Question Answering Using Dynamic Prompting and Decoding Knowledge Editing

Zhou, Z., Huang, Y., Wang, X., & Hong, X. (2025) · Data Science and Engineering · doi:10.1007/s41019-025-00291-0

Medical semantic knowledge‐integrated multitask learning network for report generation and neoadjuvant chemotherapy response prediction

Song, W. G., Fan, M., & Li, L. (2025) · Medical Physics · doi:10.1002/mp.17925

SAMBA-Net: Enhancing Sarcomere Organization Evaluation with AI-Powered Multi-Modal Learning

Chen, Y., Yang, H., Ma, S., & Guo, F. (2025) · Communications in computer and information science · doi:10.1007/978-981-95-0011-6_5

Knowledge-Enhanced Hyperbolic Language-Image Pretraining for Zero-Shot Learning

Han, L., Qiao, Z., Zhen, X., Gao, J., & Qian, Z. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-96625-5_14

Taming Masked Image Modeling for Chest X-ray Diagnosis by Incorporating Clinical Visual Priors

Zhao, Z., Wang, M., Cui, Z., Wang, S., Zhou, Q., Li, F., Wang, Q., & Shen, D. G. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-96625-5_11

MedKI: Knowledge Dual Injections for Medical Visual Question Answering

Ren, H., Chen, W., Liu, C., Ji, Y., & Li, Y. (2025) · Proceedings - International Conference on Image Processing · doi:10.1109/icip55913.2025.11084480

AGA: An adaptive group alignment framework for structured medical cross-modal representation learning

Li, W., Gong, X., Li, J., & Sun, X. (2025) · Knowledge-Based Systems · doi:10.1016/j.knosys.2025.114286

Adapter-Based Parameter-Efficient Fine-Tuning for Vision-Language Models in Radiology

Aydın, M. A., Yılmaz, M. B., Genç, F., Atlı, Ö. F., Nezhad, V. A., & Çukur, T. (2025) · Signal Processing and Communications Applications Conference (SIU) · doi:10.1109/siu66497.2025.11112489

Eliminating Non-Overlapping Semantic Misalignment for Cross-Modal Medical Retrieval

Wei, Z., Hou, Z., & Zhou, X. (2025) · IEEE Signal Processing Letters · doi:10.1109/lsp.2025.3602392

PedCLIP: A Vision-Language Model for Pediatric X-Rays with Mixture of Body Part Experts

Huy, T. D., Shoby, A., Tran, S., Xie, Y., Chen, Q., Nguyen, P. L., Gole, A., Liu, L., Perperidis, A., Friswell, M., et al. (2025) · Lecture notes in computer science · doi:10.1007/978-3-032-04971-1_46

PolarDETR: Enhancing Interpretability in Multi-modal Methods for Jawbone Lesion Detection in CBCT

Yang, Y., Chen, Z., Zhang, X., Ma, R., Li, G., Guo, Y. S., & Li, J. (2025) · Lecture notes in computer science · doi:10.1007/978-3-032-04927-8_48

Improving Cross-Modal Consistency in Multimodal Biomedical AI: A Comprehensive Review of Techniques

Basak, A., Choudhury, S. N., & Garai, P. (2025) · International Conference on Computing, Intelligence, and Application (CIACON) · doi:10.1109/ciacon65473.2025.11189769

ClinVLA: an image-text retrieval method for promoting hospital diagnosis data analysis and patient health prediction

Hao, X., Liu, J., & Yang, C. (2025) · Frontiers in Physiology · doi:10.3389/fphys.2025.1661960

Multi-modal Contrastive Learning for Medical Image Classification and Clustering

Kapić, Z., & Štajduhar, I. (2025) · Lecture notes in networks and systems · doi:10.1007/978-3-032-05159-2_2

Multi-subspace mapping and adaptive learning: MMAL-CL for cross-domain few-shot image identification across scenarios

Du, Q., Xia, X., Liu, Q., Lv, Y., Li, L., & Miao, Z. (2025) · Frontiers in Physics · doi:10.3389/fphy.2025.1681254

Vision-Language Models for Automatic Captioning and Cross-Modal Retrieval

Ounadi, I., & Schoeffmann, K. (2025) · International Workshop on Multimedia Computing for Health and Medicine (MCHM) · doi:10.1145/3728424.3760764

Self-Supervised Anatomical Consistency Learning for Vision-Grounded Medical Report Generation

Yang, L., Ni, Z., Wen, Y., Liu, Y., He, L., & Shen, H. T. (2025) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3746027.3754913

MeDKCoOp: Dual Knowledge-guided Graph Prompt Learning for Biomedical Vision-Language Models

Wang, Y., Wu, S., Gan, L., Zhang, Z., Zhang, J., Hu, Z., Zhu, H., Wu, P., & Sun, X. (2025) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3746027.3755135

Pathology-Aware Reconstruction with Discriminative Knowledge Boosting Alignment for Che-Xray Vision-Language Pre-training

Qiao, L., Gao, S., Shu, Y., Xiao, B., Li, W., & Gao, X. (2025) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3746027.3755336

A Unified Multimodal Multi-Granularity Pre-Training Framework for Fine-Grained Medical Image Analysis

Gong, Z., He, L., Zhou, N., Liao, P., Yang, H., Wu, Z., Chen, H., & Zhang, Y. (2025) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn64981.2025.11228394

MultiModal craniocerebral diagnose based on 3D CT and image reports

He, W., Chen, Q., Gao, W., Xu, H., & Wei, Z. X. (2025) · Scientific Reports · doi:10.1038/s41598-025-30249-1

VT-MFLV: Vision–Text Multimodal Feature Learning V Network for Medical Image Segmentation

Wang, W., Li, J., Ye, Z., Cai, Y., Wang, Z., & Zhang, R. (2025) · Journal of Imaging · doi:10.3390/jimaging11120425

From Sight to Insight: Enhancing Confusable Structure Segmentation via Vision-Language Mutual Prompting

Huang, Y., Zuo, Y., Xu, M., Chen, K., Wu, M., Zhang, C., Ma, Z., & Guo, J. H. (2025) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2025.3639888

Transformers in Medicine: Improving Vision-Language Alignment for Medical Image Captioning

Suresh, Y. T., Hogale, V. S., Zamfira, L.-A., & Hegde, A. (2026) · Lecture notes in electrical engineering · doi:10.1007/978-981-95-7425-4_47

DMMSA net: a dual multi-modal self-attention network for lung target areas segmentation using chest radiology images and reports

Longjiang, E., Cai, Y., Zhao, B., Zhang, M., Lin, J., & Wang, T. (2025) · Journal of King Saud University - Computer and Information Sciences · doi:10.1007/s44443-025-00402-x

Vision-Language Sliding Cross Attention for Text-Guided Pneumonia Segmentation

Yao, F., Zhang, X., Jiang, X., Xiao, Y., Fan, L., Zhou, S. K., & Liu, S. A. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-09569-5_23

RUMNet: Reconstructed Attention and Unified Multimodal Network for Medical Image Segmentation

Lv, Q., Zhang, C., & Yang, W. (2026) · Communications in computer and information science · doi:10.1007/978-981-95-4828-6_15

Hierarchical Organ-Position Attention Network for Chest X-ray and Radiology Report Retrieval

Zhou, X., Wang, Y., & Song, B. (2025) · International Conference on Digital Society and Intelligent Systems (DSInS) · doi:10.1109/dsins68311.2025.11330093

Medical Vision Language Model With Multi-granularity Alignment and Learning Data Augmentation

Gao, D., Hua, Y., Zhang, W., & Song, X. (2026) · Lecture notes in computer science · doi:10.1007/978-981-95-5634-2_34

Fine-Grained Knowledge-Guided Alignment for Medical Vision-Language Pre-Training

Pan, Y., Cheng, Y., Li, Y., Li, Q., Yuan, R., & Feng, R. (2025) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm66473.2025.11356422

TGS-LGP: Text-Guided Medical Image Segmentation Via Local-Global Perception

Ji, B., Huang, J., Xu, Z., Ou, M., Liu, T., Zeng, S., Zhou, J., & Yuan, K. (2025) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm66473.2025.11356126

DeViDe: Faceted Medical Knowledge to Enhance Vision Foundation Model Pretraining for Radiology

Luo, H., Zhou, Z., Hou, M., Royer, C., Reyes, M., Sekuboyina, A., & Menze, B. H. (2025) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm66473.2025.11357035

MMKPL-Seg: Knowledge Proxy Learning with Missing Modalities for Medical Image Segmentation

Ding, S., Fan, M., & Li, M. (2025) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm66473.2025.11356586

BiFormer-Seg: Dual-Branch Visual Encoding and Text-Guided Decoding for Radiological Segmentation

Yang, C., Shi, J., Gong, H., Duan, Y., & Yun, L. (2025) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm66473.2025.11356458

Empowering Multimodal Models via Active in-Context Learning for Test-Time Medical Imaging

Wang, F., Han, Z., & Yin, Y. (2025) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm66473.2025.11356677

PCLIM: Prototype-Based Category-Level Image-Text Multimodal Learning Method for Fetal Cardiac Ultrasound Imaging Analysis

Chen, X., Tong, L., & Du, B. (2025) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm66473.2025.11357174

Classifying Pulmonary Diseases Using Small Multimodal Model on X-Ray Images and Reports

Thai, M. K., & Tran, D.-K. (2025) · RIVF International Conference on Computing and Communication Technologies (RIVF) · doi:10.1109/rivf68649.2025.11365036

MATEX: Multi-scale Attention and Text-Guided Explainability of Medical Vision-Language Models

Imran, M., Lee, C., & Lee, Y. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-17611-0_14

Distribution-Based Masked Medical Vision-Language Model Using Structured Reports

Gowda, S. N., Zhang, R., Gu, X., Weng, Y., & Yang, L. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-17611-0_1

A self-supervised representation-transfer multimodal learning for automated diagnosis of Developmental Dysplasia of the Hip

Yao, J., Su, Z., Jian, C., Lin, G., Gao, Z., Su, C., Xu, S., Chen, Y., & Cai, D. (2026) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2026.109868

Unified Supervision for Vision-Language Modeling in 3D Computed Tomography

Lee, H.-C., Liu, Z., Ahmed, H., Kim, S., Huver, S. D., Nath, V., Fayad, Z. A., Deyer, T. W., & Mei, X. (2025) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw69036.2025.00700

Cross modal global local representation learning from radiology reports and x-ray chest images

Hadjiyski, N., Vosoughi, A., & Wismüller, A. (2023) · SPIE Medical Imaging: Computer-Aided Diagnosis · doi:10.1117/12.2654520 · Cited by 6

Paying Per-Label Attention for Multi-label Extraction from Radiology Reports

Schrempf, P., Watson, H. I., Mikhael, S. S., Pajak, M., Falis, M., Lisowska, A., Muir, K. W., Harris‐Birtill, D., & O’Neil, A. Q. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-61166-8_29 · Cited by 7

LIMITR: Leveraging Local Information for Medical Image-Text Representation

Dawidowicz, G., Hirsch, E., & Tal, A. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.01935 · Cited by 18

Label the many with a few: Semi-automatic medical image modality discovery in a large image collection

Vajda, S., You, D., Antani, S., & Thoma, G. R. (2014) · IEEE Symposium on Computational Intelligence in Healthcare and e-health (CICARE) · doi:10.1109/cicare.2014.7007850 · Cited by 5

Joint Learning of Localized Representations from Medical Images and Reports

Müller, P., Kaissis, G. A., Zou, C., & Rückert, D. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-19809-0_39 · Cited by 30