Copertina

MLIP: Medical Language-Image Pre-training with Masked Local Representation Learning

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Liu, Jiarun, Zhou, Hong-Yu, Li, Cheng, Huang, Weijian, Yang, Hao, Liang, Yong, Wang, Shanshan
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Computer Vision and Pattern Recognition
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Enhancing Representation in Radiography-Reports Foundation Model: A Granular Alignment Algorithm Using Masked Contrastive Learning
di: Huang, Weijian, et al.
Pubblicazione: (2023)

Enhancing Representation in Medical Vision-Language Foundation Models via Multi-Scale Information Extraction Techniques
di: Huang, Weijian, et al.
Pubblicazione: (2024)

BioVFM-21M: Benchmarking and Scaling Self-Supervised Vision Foundation Models for Biomedical Image Analysis
di: Liu, Jiarun, et al.
Pubblicazione: (2025)

Enhancing the vision-language foundation model with key semantic knowledge-emphasized report refinement
di: Huang, Weijian, et al.
Pubblicazione: (2024)

MLIP: Enhancing Medical Visual Representation with Divergence Encoder and Knowledge-guided Contrastive Learning
di: Li, Zhe, et al.
Pubblicazione: (2024)

PLIP: Language-Image Pre-training for Person Representation Learning
di: Zuo, Jialong, et al.
Pubblicazione: (2023)

Multimodal self-supervised learning for lesion localization
di: Yang, Hao, et al.
Pubblicazione: (2024)

MaskedCLIP: Bridging the Masked and CLIP Space for Semi-Supervised Medical Vision-Language Pre-training
di: Zhu, Lei, et al.
Pubblicazione: (2025)

Pre-trained Models Succeed in Medical Imaging with Representation Similarity Degradation
di: Zu, Wenqiang, et al.
Pubblicazione: (2025)

Progressive Local Alignment for Medical Multimodal Pre-training
di: Yan, Huimin, et al.
Pubblicazione: (2025)

MLIP: Efficient Multi-Perspective Language-Image Pretraining with Exhaustive Data Utilization
di: Zhang, Yu, et al.
Pubblicazione: (2024)

Bias-constrained multimodal intelligence for equitable and reliable clinical AI
di: Li, Cheng, et al.
Pubblicazione: (2026)

Advancing Medical Radiograph Representation Learning: A Hybrid Pre-training Paradigm with Multilevel Semantic Granularity
di: Jiang, Hanqi, et al.
Pubblicazione: (2024)

Masks and Manuscripts: Advancing Medical Pre-training with End-to-End Masking and Narrative Structuring
di: Gowda, Shreyank N, et al.
Pubblicazione: (2024)

VELVET-Med: Vision and Efficient Language Pre-training for Volumetric Imaging Tasks in Medicine
di: Zhang, Ziyang, et al.
Pubblicazione: (2025)

Semantics-enhanced Cross-modal Masked Image Modeling for Vision-Language Pre-training
di: Liu, Haowei, et al.
Pubblicazione: (2024)

A multi-modal vision-language model for generalizable annotation-free pathology localization
di: Yang, Hao, et al.
Pubblicazione: (2024)

MedUnifier: Unifying Vision-and-Language Pre-training on Medical Data with Vision Generation Task using Discrete Visual Representations
di: Zhang, Ziyang, et al.
Pubblicazione: (2025)

Unified Medical Image Pre-training in Language-Guided Common Semantic Space
di: He, Xiaoxuan, et al.
Pubblicazione: (2023)

Muskie: Multi-view Masked Image Modeling for 3D Vision Pre-training
di: Li, Wenyu, et al.
Pubblicazione: (2025)

Masked Clustering Prediction for Unsupervised Point Cloud Pre-training
di: Ren, Bin, et al.
Pubblicazione: (2025)

Efficient Vision-Language Pre-training by Cluster Masking
di: Wei, Zihao, et al.
Pubblicazione: (2024)

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction
di: Song, Dongning, et al.
Pubblicazione: (2024)

Pre-trained Visual Dynamics Representations for Efficient Policy Learning
di: Luo, Hao, et al.
Pubblicazione: (2024)

Towards Scalable Language-Image Pre-training for 3D Medical Imaging
di: Zhao, Chenhui, et al.
Pubblicazione: (2025)

MiM: Mask in Mask Self-Supervised Pre-Training for 3D Medical Image Analysis
di: Zhuang, Jiaxin, et al.
Pubblicazione: (2024)

Focus on Texture: Rethinking Pre-training in Masked Autoencoders for Medical Image Classification
di: Madan, Chetan, et al.
Pubblicazione: (2025)

Winner Team Mia at TextVQA Challenge 2021: Vision-and-Language Representation Learning with Pre-trained Sequence-to-Sequence Model
di: Qiao, Yixuan, et al.
Pubblicazione: (2021)

Pre-training Everywhere: Parameter-Efficient Fine-Tuning for Medical Image Analysis via Target Parameter Pre-training
di: Lei, Xingliang, et al.
Pubblicazione: (2024)

MedFILIP: Medical Fine-grained Language-Image Pre-training
di: Liang, Xinjie, et al.
Pubblicazione: (2025)

SelfMedHPM: Self Pre-training With Hard Patches Mining Masked Autoencoders For Medical Image Segmentation
di: Lv, Yunhao, et al.
Pubblicazione: (2025)

MMCLIP: Cross-modal Attention Masked Modelling for Medical Language-Image Pre-Training
di: Wu, Biao, et al.
Pubblicazione: (2024)

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training
di: Wang, Rongsheng, et al.
Pubblicazione: (2026)

Data-efficient Event Camera Pre-training via Disentangled Masked Modeling
di: Huang, Zhenpeng, et al.
Pubblicazione: (2024)

Sculpting Holistic 3D Representation in Contrastive Language-Image-3D Pre-training
di: Gao, Yipeng, et al.
Pubblicazione: (2023)

Hierarchical Fusion and Joint Aggregation: A Multi-Level Feature Representation Method for AIGC Image Quality Assessment
di: Meng, Linghe, et al.
Pubblicazione: (2025)

Universal Image Restoration Pre-training via Masked Degradation Classification
di: Hu, JiaKui, et al.
Pubblicazione: (2025)

Multimodal Medical Image Classification via Synergistic Learning Pre-training
di: Lin, Qinghua, et al.
Pubblicazione: (2025)

Visual-Language Model Knowledge Distillation Method for Image Quality Assessment
di: Hou, Yongkang, et al.
Pubblicazione: (2025)

Centered Masking for Language-Image Pre-Training
di: Liang, Mingliang, et al.
Pubblicazione: (2024)