Cover Image

Alleviating Textual Reliance in Medical Language-guided Segmentation via Prototype-driven Semantic Approximation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ye, Shuchang, Naseem, Usman, Meng, Mingyuan, Kim, Jinman
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

MedCFVQA: A Causal Approach to Mitigate Modality Preference Bias in Medical Visual Question Answering
by: Ye, Shuchang, et al.
Published: (2025)

RadGenome-Anatomy: A Large-Scale Anatomy-Labeled Chest Radiograph Dataset via Physically Grounded Volumetric Projection
by: Ye, Shuchang, et al.
Published: (2026)

Dynamic Traceback Learning for Medical Report Generation
by: Ye, Shuchang, et al.
Published: (2024)

Language-guided Medical Image Segmentation with Target-informed Multi-level Contrastive Alignments
by: Li, Mingjian, et al.
Published: (2024)

SGSeg: Enabling Text-free Inference in Language-guided Segmentation of Chest X-rays via Self-guidance
by: Ye, Shuchang, et al.
Published: (2024)

Intersectional Fairness in Vision-Language Models for Medical Image Disease Classification
by: Zhang, Yupeng, et al.
Published: (2025)

Bridging the Semantic Gaps: Improving Medical VQA Consistency with LLM-Augmented Question Sets
by: Ma, Yongpei, et al.
Published: (2025)

Correlation-aware Coarse-to-fine MLPs for Deformable Medical Image Registration
by: Meng, Mingyuan, et al.
Published: (2024)

SMPL-GPTexture: Dual-View 3D Human Texture Estimation using Text-to-Image Generation Models
by: Tu, Mingxiao, et al.
Published: (2025)

MAISY: Motion-Aware Image SYnthesis for Medical Image Motion Correction
by: Zhang, Andrew, et al.
Published: (2025)

Advancing Deformable Medical Image Registration with Multi-axis Cross-covariance Attention
by: Meng, Mingyuan, et al.
Published: (2024)

AutoFuse: Automatic Fusion Networks for Deformable Medical Image Registration
by: Meng, Mingyuan, et al.
Published: (2023)

Enhancing medical vision-language contrastive learning via inter-matching relation modelling
by: Li, Mingjian, et al.
Published: (2024)

IMPROVE: Improving Medical Plausibility without Reliance on HumanValidation -- An Enhanced Prototype-Guided Diffusion Framework
by: Shandilya, Anurag, et al.
Published: (2024)

SPENet: Self-guided Prototype Enhancement Network for Few-shot Medical Image Segmentation
by: Fan, Chao, et al.
Published: (2025)

Beyond Calibration: Confounding Pathology Limits Foundation Model Specificity in Abdominal Trauma CT
by: Raythatha, Jineel H, et al.
Published: (2026)

Toward Next-generation Medical Vision Backbones: Modeling Finer-grained Long-range Visual Dependency
by: Meng, Mingyuan
Published: (2025)

Cross-Modal Conditioned Reconstruction for Language-guided Medical Image Segmentation
by: Huang, Xiaoshuang, et al.
Published: (2024)

LVMed-R2: Perception and Reflection-driven Complex Reasoning for Medical Report Generation
by: Wang, Hao, et al.
Published: (2025)

Is Foreground Prototype Sufficient? Few-Shot Medical Image Segmentation with Background-Fused Prototype
by: Tang, Song, et al.
Published: (2024)

Hyper-Fusion Network for Semi-Automatic Segmentation of Skin Lesions
by: Bi, Lei, et al.
Published: (2024)

MRG-R1: Reinforcement Learning for Clinically Aligned Medical Report Generation
by: Wang, Pengyu, et al.
Published: (2025)

Domain-invariant Prototypes for Semantic Segmentation
by: Yang, Zhengeng, et al.
Published: (2022)

Reducing Semantic Ambiguity In Domain Adaptive Semantic Segmentation Via Probabilistic Prototypical Pixel Contrast
by: Hao, Xiaoke, et al.
Published: (2024)

A Dual-branch Self-supervised Representation Learning Framework for Tumour Segmentation in Whole Slide Images
by: Wang, Hao, et al.
Published: (2023)

Medal S: Spatio-Textual Prompt Model for Medical Segmentation
by: Shi, Pengcheng, et al.
Published: (2025)

Transfer or Self-Supervised? Bridging the Performance Gap in Medical Imaging
by: Zhao, Zehui, et al.
Published: (2024)

Query-guided Prototype Evolution Network for Few-Shot Segmentation
by: Cong, Runmin, et al.
Published: (2024)

Can Textual Semantics Mitigate Sounding Object Segmentation Preference?
by: Wang, Yaoting, et al.
Published: (2024)

Tied Prototype Model for Few-Shot Medical Image Segmentation
by: Kim, Hyeongji, et al.
Published: (2025)

A Review of Predictive and Contrastive Self-supervised Learning for Medical Images
by: Wang, Wei-Chien, et al.
Published: (2023)

Prototypical Progressive Alignment and Reweighting for Generalizable Semantic Segmentation
by: Zhang, Yuhang, et al.
Published: (2025)

Prototype-Based Low Altitude UAV Semantic Segmentation
by: Zhang, Da, et al.
Published: (2026)

Multi-Modal Prototypes for Open-World Semantic Segmentation
by: Yang, Yuhuan, et al.
Published: (2023)

Adaptive Prototype Replay for Class Incremental Semantic Segmentation
by: Zhu, Guilin, et al.
Published: (2024)

ProtoSeg: Interpretable Semantic Segmentation with Prototypical Parts
by: Sacha, Mikołaj, et al.
Published: (2023)

Probabilistic Prototype Calibration of Vision-Language Models for Generalized Few-shot Semantic Segmentation
by: Liu, Jie, et al.
Published: (2025)

Divide, Conquer and Unite: Hierarchical Style-Recalibrated Prototype Alignment for Federated Medical Segmentation
by: Zhao, Xingyue, et al.
Published: (2025)

AdaMSS: Adaptive Multi-Modality Segmentation-to-Survival Learning for Survival Outcome Prediction from PET/CT Images
by: Meng, Mingyuan, et al.
Published: (2023)

Few-Shot Medical Image Segmentation with High-Fidelity Prototypes
by: Tang, Song, et al.
Published: (2024)