Cover Image

MedP-CLIP: Medical CLIP with Region-Aware Prompt Integration

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Peng, Jiahui, Yao, He, Li, Jingwen, Su, Yanzhou, Ju, Sibo, Lu, Yujie, Ye, Jin, Lu, Hongchun, Li, Xue, Jiang, Lincheng, Zhu, Min, Cheng, Junlong
Format:	Preprint
Published:	2026
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

SegMoTE: Token-Level Mixture of Experts for Medical Image Segmentation
by: Lu, Yujie, et al.
Published: (2026)

BadCLIP: Trigger-Aware Prompt Learning for Backdoor Attacks on CLIP
by: Bai, Jiawang, et al.
Published: (2023)

MedSAD-CLIP: Supervised CLIP with Token-Patch Cross-Attention for Medical Anomaly Detection and Segmentation
by: Tran, Thuy Truong, et al.
Published: (2026)

RegionMed-CLIP: A Region-Aware Multimodal Contrastive Learning Pre-trained Model for Medical Image Understanding
by: Fang, Tianchen, et al.
Published: (2025)

VTD-CLIP: Video-to-Text Discretization via Prompting CLIP
by: Zhu, Wencheng, et al.
Published: (2025)

C2P-CLIP: Injecting Category Common Prompt in CLIP to Enhance Generalization in Deepfake Detection
by: Tan, Chuangchuang, et al.
Published: (2024)

Prompt Tuning for CLIP on the Pretrained Manifold
by: Yang, Xi, et al.
Published: (2026)

Enhancing LLMs' Reasoning-Intensive Multimedia Search Capabilities through Fine-Tuning and Reinforcement Learning
by: Li, Jinzheng, et al.
Published: (2025)

Continual Learning on CLIP via Incremental Prompt Tuning with Intrinsic Textual Anchors
by: Lu, Haodong, et al.
Published: (2025)

DeCLIP: Decoupled Prompting for CLIP-based Multi-Label Class-Incremental Learning
by: Du, Kaile, et al.
Published: (2025)

MediCLIP: Adapting CLIP for Few-shot Medical Image Anomaly Detection
by: Zhang, Ximiao, et al.
Published: (2024)

Interactive Medical Image Segmentation: A Benchmark Dataset and Baseline
by: Cheng, Junlong, et al.
Published: (2024)

CLIP-Guided Unsupervised Semantic-Aware Exposure Correction
by: Wu, Puzhen, et al.
Published: (2026)

MoP-CLIP: A Mixture of Prompt-Tuned CLIP Models for Domain Incremental Learning
by: Nicolas, Julien, et al.
Published: (2023)

AA-CLIP: Enhancing Zero-shot Anomaly Detection via Anomaly-Aware CLIP
by: Ma, Wenxin, et al.
Published: (2025)

MedSAE: Dissecting MedCLIP Representations with Sparse Autoencoders
by: Renzulli, Riccardo, et al.
Published: (2025)

AD-CLIP: Adapting Domains in Prompt Space Using CLIP
by: Singha, Mainak, et al.
Published: (2023)

Backdoor Attack on Unpaired Medical Image-Text Foundation Models: A Pilot Study on MedCLIP
by: Jin, Ruinan, et al.
Published: (2024)

DialCLIP: Empowering CLIP as Multi-Modal Dialog Retriever
by: Yin, Zhichao, et al.
Published: (2024)

AttriPrompt: Dynamic Prompt Composition Learning for CLIP
by: Zhan, Qiqi, et al.
Published: (2025)

IQE-CLIP: Instance-aware Query Embedding for Zero-/Few-shot Anomaly Detection in Medical Domain
by: Huang, Hong, et al.
Published: (2025)

MadCLIP: Few-shot Medical Anomaly Detection with CLIP
by: Shiri, Mahshid, et al.
Published: (2025)

Bringing CLIP to the Clinic: Dynamic Soft Labels and Negation-Aware Learning for Medical Analysis
by: Ko, Hanbin, et al.
Published: (2025)

Integrating MedCLIP and Cross-Modal Fusion for Automatic Radiology Report Generation
by: Han, Qianhao, et al.
Published: (2024)

Envisioning MedCLIP: A Deep Dive into Explainability for Medical Vision-Language Models
by: Hashmi, Anees Ur Rehman, et al.
Published: (2024)

MedCLIP-SAMv2: Towards Universal Text-Driven Medical Image Segmentation
by: Koleilat, Taha, et al.
Published: (2024)

MedCLIP-SAM: Bridging Text and Image Towards Universal Medical Image Segmentation
by: Koleilat, Taha, et al.
Published: (2024)

GenCLIP: Generalizing CLIP Prompts for Zero-shot Anomaly Detection
by: Kim, Donghyeong, et al.
Published: (2025)

Enhancing CLIP with CLIP: Exploring Pseudolabeling for Limited-Label Prompt Tuning
by: Menghini, Cristina, et al.
Published: (2023)

CardiacCLIP: Video-based CLIP Adaptation for LVEF Prediction in a Few-shot Manner
by: Du, Yao, et al.
Published: (2025)

CLIP in Medical Imaging: A Survey
by: Zhao, Zihao, et al.
Published: (2023)

CultureCLIP: Empowering CLIP with Cultural Awareness through Synthetic Images and Contextualized Captions
by: Huang, Yuchen, et al.
Published: (2025)

KAnoCLIP: Zero-Shot Anomaly Detection through Knowledge-Driven Prompt Learning and Enhanced Cross-Modal Integration
by: Li, Chengyuan, et al.
Published: (2025)

SAM-Med3D: Towards General-purpose Segmentation Models for Volumetric Medical Images
by: Wang, Haoyu, et al.
Published: (2023)

CLIP-SENet: CLIP-based Semantic Enhancement Network for Vehicle Re-identification
by: Lu, Liping, et al.
Published: (2025)

DrugCLIP: Contrastive Drug-Disease Interaction For Drug Repurposing
by: Lu, Yingzhou, et al.
Published: (2024)

AdaCLIP: Adapting CLIP with Hybrid Learnable Prompts for Zero-Shot Anomaly Detection
by: Cao, Yunkang, et al.
Published: (2024)

ViP$^2$-CLIP: Visual-Perception Prompting with Unified Alignment for Zero-Shot Anomaly Detection
by: Yang, Ziteng, et al.
Published: (2025)

SkinCLIP-VL: Consistency-Aware Vision-Language Learning for Multimodal Skin Cancer Diagnosis
by: Lu, Zhixiang, et al.
Published: (2026)

CLIP-GS: CLIP-Informed Gaussian Splatting for View-Consistent 3D Indoor Semantic Understanding
by: Liao, Guibiao, et al.
Published: (2024)