awesome-medical-vision-and-language-pretraining

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awesome-medical-vision-and-language-pretraining

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The collection of medical VLP papars

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# awesome-medical-vision-and-language-pretraining
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### The collection of medical VLP papars (Chest X-ray)
✨ We will promptly update the relevant papers. Please feel free to contact me to add links or to discuss this area with me.

### 2024
 - [**arxiv 2024**] [**ECAMP**] ECAMP: Entity-centered Context-aware Medical Vision Language Pre-training [[pdf]](https://arxiv.org/pdf/2312.13316.pdf) [[code]](https://github.com/ToniChopp/ECAMP)
 - [**arxiv 2024**] [**MeDSLIP**] MeDSLIP: Medical Dual-Stream Language-Image Pre-training for Fine-grained Alignment [[pdf]](https://arxiv.org/pdf/2403.10635.pdf)
 - [**CVPR 2024**] [**CARZeroP**] CARZero: Cross-Attention Alignment for Radiology Zero-Shot Classification [[pdf]](https://arxiv.org/pdf/2402.17417.pdf) [[code]](https://github.com/laihaoran/CARZero)
 - [**CVPR 2024**] [**MAVL**] DecomposingDiseaseDescriptionsforEnhancedPathologyDetection:A Multi-AspectVision-LanguagePre-trainingFramework [[pdf]](https://arxiv.org/pdf/2403.07636.pdf) [[code]](https://github.com/HieuPhan33/MAVL)
 - [**CVPR 2024**] [**MLIP**] MLIP: Enhancing Medical Visual Representation with Divergence Encoder and Knowledge-guided Contrastive Learning [[pdf]](https://arxiv.org/pdf/2402.02045) [[code]](https://github.com/gentlefress/MLIP)
 - [**ICML 2024**] [**Med-ST**] Unlocking the Power of Spatial and Temporal Information in Medical Multimodal Pre-training [[pdf]](https://arxiv.org/pdf/2405.19654) [[code]](https://github.com/SVT-Yang/MedST)
 - [**MICCAI 2024**] [**ASG**]  Anatomical Structure-Guided Medical Vision-Language Pre-training [[pdf]](https://arxiv.org/pdf/2403.09294) [[code]](https://github.com/ASGMVLP/ASGMVLP_CODE)
 
### 2023
 - [**ICLR 2023**] [**MRM**] Advancing Radiograph Representation Learning with Masked Record Modeling [[pdf]](https://openreview.net/pdf?id=w-x7U26GM7j) [[code]](https://github.com/RL4M/MRM-pytorch)
 - [**CVPR 2023**] [**BioViL-T**] Learning to Exploit Temporal Structure for Biomedical Vision–Language Processing [[pdf]](https://arxiv.org/pdf/2301.04558.pdf) [[code]](https://github.com/microsoft/hi-ml/tree/main/hi-ml-multimodal)
 - [**MICCAI 2023**] [**CXR-CLIP**] Toward Large Scale Chest X-ray Language-Image Pre-training [[pdf]](https://arxiv.org/pdf/2310.13292.pdf) [[code]](https://github.com/kakaobrain/cxr-clip)
 - [**MICCAI 2023**] [**M-FLAG**] M-FLAG: Medical Vision-Language Pre-training with Frozen Language Models and Latent Space Geometry Optimization [[pdf]](https://arxiv.org/pdf/2307.08347.pdf) [[code]](https://github.com/cheliu-computation/M-FLAG-MICCAI2023)
 - [**MICCAI 2023**] [**KoBo**] Knowledge Boosting: Rethinking Medical Contrastive Vision-Language Pre-Training [[pdf]](https://arxiv.org/pdf/2307.07246) [[code]](https://github.com/ChenXiaoFei-CS/KoBo)
 - [**MICCAI-ws 2023**] [**K-Diag**] K-Diag: Knowledge-enhanced Disease Diagnosis in Radiographic Imaging [[pdf]](https://arxiv.org/pdf/2302.11557.pdf) [[code]](https://github.com/MediaBrain-SJTU/K-Diag)
 - [**ICCV 2023**] [**MedKLIP**] MedKLIP: Medical Knowledge Enhanced Language-Image Pre-Training in Radiology [[pdf]](https://arxiv.org/pdf/2301.02228.pdf) [[code]](https://github.com/MediaBrain-SJTU/MedKLIP)
 - [**ICCV 2023**] [**PTUnifier**] Towards Unifying Medical Vision-and-Language Pre-training via Soft Prompts [[pdf]](https://arxiv.org/pdf/2302.08958.pdf) [[code]](https://github.com/zhjohnchan/PTUnifier)
 - [**ICCV 2023**] [**PRIOR**] PRIOR: Prototype Representation Joint Learning from Medical Images and Reports [[pdf]](https://arxiv.org/pdf/2307.12577.pdf) [[code]](https://github.com/QtacierP/PRIOR)
 - [**ICCV 2023**] [**LIMITR**] LIMITR: Leveraging Local Information for Medical Image-Text Representation [[pdf]](https://arxiv.org/pdf/2303.11755) 
 - [**Nature Com 2023**] [**KAD**]  Knowledge-enhanced Visual-Language Pre-training on Chest Radiology Images [[pdf]](https://arxiv.org/pdf/2302.14042.pdf) [[code]](https://github.com/xiaoman-zhang/KAD)
 - [**MIA 2023**] [**SAT**] Improving Medical Vision-Language Contrastive Pretraining With Semantics-Aware Triage [[pdf]](https://ieeexplore.ieee.org/document/10182304) [[code]](https://github.com/liubo105/SAT)
 - [**arxiv 2023**] [**MOTOR**] Towards Medical Artificial General Intelligence via Knowledge-Enhanced Multimodal Pretraining [[pdf]](https://arxiv.org/pdf/2304.14204.pdf) [[code]](https://github.com/chenzcv7/MOTOR)

### 2022
 - [**MICCAI 2022**] [**BFSPR**] Breaking with Fixed Set Pathology Recognition through Report-Guided Contrastive Training [[pdf]](https://arxiv.org/pdf/2205.07139.pdf) 
 - [**MICCAI 2022**] [**M3AE**] Multi-Modal Masked Autoencoders for Medical Vision-and-Language Pre-Training [[pdf]](https://arxiv.org/pdf/2209.07098.pdf) [[code]](https://github.com/zhjohnchan/M3AE)
 - [**ACM MM 2022**] [**ARL**] Align, Reason and Learn: Enhancing Medical Vision-and-Language Pre-training with Knowledge [[pdf]](https://arxiv.org/pdf/2209.07118.pdf) [[code]](https://github.com/zhjohnchan/ARL)
 - [**EMNLP 2022**] [**MedCLIP**] Contrastive Learning from Unpaired Medical Images and Text [[pdf]](https://arxiv.org/pdf/2210.10163.pdf) [[code]](https://github.com/RyanWangZf/MedCLIP)
 - [**ECCV 2022**] [**BioViL**] Making the Most of Text Semantics to Improve Biomedical Vision–Language Processing [[pdf]](https://arxiv.org/pdf/2204.09817.pdf) [[code]](https://hi-ml.readthedocs.io/en/latest/multimodal.html)
 - [**ECCV 2022**] [**LoVT**] Joint Learning of Localized Representations from Medical Images and Reports [[pdf]](https://arxiv.org/pdf/2112.02889.pdf)
 - [**NIPS 2022**] [**MGCA**] Multi-Granularity Cross-modal Alignment for Generalized Medical Visual Representation Learning [[pdf]](https://arxiv.org/pdf/2210.06044.pdf) [[code]](https://github.com/HKU-MedAI/MGCA)

### 2021
- [**PMLR 2022(arxiv 2020)**] [**ConViRT**] Contrastive Learning of Medical Visual Representations from Paired Images and Text [[pdf]](https://arxiv.org/pdf/2010.00747.pdf) [[code]](https://github.com/edreisMD/ConVIRT-pytorch)
- [**ICCV 2021**] [**GLoRIA**] AMultimodal Global-Local Representation Learning Framework for Label-efficient Medical Image Recognition [[pdf]](https://openaccess.thecvf.com/content/ICCV2021/papers/Huang_GLoRIA_A_Multimodal_Global-Local_Representation_Learning_Framework_for_Label-Efficient_Medical_ICCV_2021_paper.pdf) [[code]](https://github.com/marshuang80/gloria)

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