Saved in:
| Main Authors: | Phuntsho, Karma, Abdullah, Lee, Kyungmi, Lee, Ickjai, Ahn, Euijoon |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2603.14271 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Adaptation of Foundation Models for Medical Image Analysis: Strategies, Challenges, and Future Directions
by: Phuntsho, Karma, et al.
Published: (2025)
by: Phuntsho, Karma, et al.
Published: (2025)
Computationally Efficient Diffusion Models in Medical Imaging: A Comprehensive Review
by: Abdullah, et al.
Published: (2025)
by: Abdullah, et al.
Published: (2025)
GVT2RPM: An Empirical Study for General Video Transformer Adaptation to Remote Physiological Measurement
by: Wang, Hao, et al.
Published: (2024)
by: Wang, Hao, et al.
Published: (2024)
A Review of Predictive and Contrastive Self-supervised Learning for Medical Images
by: Wang, Wei-Chien, et al.
Published: (2023)
by: Wang, Wei-Chien, et al.
Published: (2023)
A Dual-branch Self-supervised Representation Learning Framework for Tumour Segmentation in Whole Slide Images
by: Wang, Hao, et al.
Published: (2023)
by: Wang, Hao, et al.
Published: (2023)
Clinical-grade Multi-Organ Pathology Report Generation for Multi-scale Whole Slide Images via a Semantically Guided Medical Text Foundation Model
by: Tan, Jing Wei, et al.
Published: (2024)
by: Tan, Jing Wei, et al.
Published: (2024)
Multimodal Generative AI with Autoregressive LLMs for Human Motion Understanding and Generation: A Way Forward
by: Islam, Muhammad, et al.
Published: (2025)
by: Islam, Muhammad, et al.
Published: (2025)
From Adaptation to Generalization: Adaptive Visual Prompting for Medical Image Segmentation
by: Çetinkaya, Evren, et al.
Published: (2026)
by: Çetinkaya, Evren, et al.
Published: (2026)
Scaling Down to Scale Up: Towards Operationally-Efficient and Deployable Clinical Models via Cross-Modal Low-Rank Adaptation for Medical Vision-Language Models
by: Alzubaidi, Thuraya, et al.
Published: (2025)
by: Alzubaidi, Thuraya, et al.
Published: (2025)
Text-guided Foundation Model Adaptation for Long-Tailed Medical Image Classification
by: Li, Sirui, et al.
Published: (2024)
by: Li, Sirui, et al.
Published: (2024)
Are Vision Foundation Models Ready for Out-of-the-Box Medical Image Registration?
by: Gu, Hanxue, et al.
Published: (2025)
by: Gu, Hanxue, et al.
Published: (2025)
Stroke Lesion Segmentation in Clinical Workflows: A Modular, Lightweight, and Deployment-Ready Tool
by: Kerverdo, Yann, et al.
Published: (2025)
by: Kerverdo, Yann, et al.
Published: (2025)
Benchmarking Pathology Foundation Models: Adaptation Strategies and Scenarios
by: Lee, Jeaung, et al.
Published: (2024)
by: Lee, Jeaung, et al.
Published: (2024)
Few-Shot Adaptation of Training-Free Foundation Model for 3D Medical Image Segmentation
by: He, Xingxin, et al.
Published: (2025)
by: He, Xingxin, et al.
Published: (2025)
FRoundation: Are Foundation Models Ready for Face Recognition?
by: Chettaoui, Tahar, et al.
Published: (2024)
by: Chettaoui, Tahar, et al.
Published: (2024)
Z-SSMNet: Zonal-aware Self-supervised Mesh Network for Prostate Cancer Detection and Diagnosis with Bi-parametric MRI
by: Yuan, Yuan, et al.
Published: (2022)
by: Yuan, Yuan, et al.
Published: (2022)
RobustMedSAM: Degradation-Resilient Medical Image Segmentation via Robust Foundation Model Adaptation
by: Li, Jieru, et al.
Published: (2026)
by: Li, Jieru, et al.
Published: (2026)
Efficient Self-Supervised Adaptation for Medical Image Analysis
by: Sorkhei, Moein, et al.
Published: (2025)
by: Sorkhei, Moein, et al.
Published: (2025)
Trade-offs in Cross-Domain Generalization of Foundation Model Fine-Tuned for Biometric Applications
by: Chettaoui, Tahar, et al.
Published: (2025)
by: Chettaoui, Tahar, et al.
Published: (2025)
Building Universal Foundation Models for Medical Image Analysis with Spatially Adaptive Networks
by: Luo, Lingxiao, et al.
Published: (2023)
by: Luo, Lingxiao, et al.
Published: (2023)
MedFoundationHub: A Lightweight and Secure Toolkit for Deploying Medical Vision Language Foundation Models
by: Li, Xiao, et al.
Published: (2025)
by: Li, Xiao, et al.
Published: (2025)
Governance-Ready Small Language Models for Medical Imaging: Prompting, Abstention, and PACS Integration
by: Wang, Yiting, et al.
Published: (2025)
by: Wang, Yiting, et al.
Published: (2025)
A Probabilistic Segment Anything Model for Ambiguity-Aware Medical Image Segmentation
by: Ward, Tyler, et al.
Published: (2025)
by: Ward, Tyler, et al.
Published: (2025)
Single GPU Task Adaptation of Pathology Foundation Models for Whole Slide Image Analysis
by: Kumar, Neeraj, et al.
Published: (2025)
by: Kumar, Neeraj, et al.
Published: (2025)
On the Interplay of Human-AI Alignment,Fairness, and Performance Trade-offs in Medical Imaging
by: Luo, Haozhe, et al.
Published: (2025)
by: Luo, Haozhe, et al.
Published: (2025)
MAFM^3: Modular Adaptation of Foundation Models for Multi-Modal Medical AI
by: Qazi, Mohammad Areeb, et al.
Published: (2025)
by: Qazi, Mohammad Areeb, et al.
Published: (2025)
Citrus-V: Advancing Medical Foundation Models with Unified Medical Image Grounding for Clinical Reasoning
by: Wang, Guoxin, et al.
Published: (2025)
by: Wang, Guoxin, et al.
Published: (2025)
Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis
by: Qu, Jingguo, et al.
Published: (2025)
by: Qu, Jingguo, et al.
Published: (2025)
Performance-Efficiency Trade-off for Fashion Image Retrieval
by: Hurtado, Julio, et al.
Published: (2025)
by: Hurtado, Julio, et al.
Published: (2025)
Domain Adaptation for Big Data in Agricultural Image Analysis: A Comprehensive Review
by: Hu, Xing, et al.
Published: (2025)
by: Hu, Xing, et al.
Published: (2025)
Blackbox Adaptation for Medical Image Segmentation
by: Paranjape, Jay N., et al.
Published: (2024)
by: Paranjape, Jay N., et al.
Published: (2024)
Collaborative Learning with Multiple Foundation Models for Source-Free Domain Adaptation
by: Lee, Huisoo, et al.
Published: (2025)
by: Lee, Huisoo, et al.
Published: (2025)
Towards Scalable Language-Image Pre-training for 3D Medical Imaging
by: Zhao, Chenhui, et al.
Published: (2025)
by: Zhao, Chenhui, et al.
Published: (2025)
LLaVA Needs More Knowledge: Retrieval Augmented Natural Language Generation with Knowledge Graph for Explaining Thoracic Pathologies
by: Hamza, Ameer, et al.
Published: (2024)
by: Hamza, Ameer, et al.
Published: (2024)
Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data
by: Mukherjee, Shubhabrata, et al.
Published: (2025)
by: Mukherjee, Shubhabrata, et al.
Published: (2025)
GenMix: Combining Generative and Mixture Data Augmentation for Medical Image Classification
by: Lee, Hansang, et al.
Published: (2024)
by: Lee, Hansang, et al.
Published: (2024)
SemanticDraw: Towards Real-Time Interactive Content Creation from Image Diffusion Models
by: Lee, Jaerin, et al.
Published: (2024)
by: Lee, Jaerin, et al.
Published: (2024)
Native Intelligence Emerges from Large-Scale Clinical Practice: A Retinal Foundation Model with Deployment Efficiency
by: Guo, Jia, et al.
Published: (2025)
by: Guo, Jia, et al.
Published: (2025)
Using Foundation Models as Pseudo-Label Generators for Pre-Clinical 4D Cardiac CT Segmentation
by: Rickmann, Anne-Marie, et al.
Published: (2025)
by: Rickmann, Anne-Marie, et al.
Published: (2025)
Vision Foundation Models in Medical Image Analysis: Advances and Challenges
by: Liang, Pengchen, et al.
Published: (2025)
by: Liang, Pengchen, et al.
Published: (2025)
Similar Items
-
Adaptation of Foundation Models for Medical Image Analysis: Strategies, Challenges, and Future Directions
by: Phuntsho, Karma, et al.
Published: (2025) -
Computationally Efficient Diffusion Models in Medical Imaging: A Comprehensive Review
by: Abdullah, et al.
Published: (2025) -
GVT2RPM: An Empirical Study for General Video Transformer Adaptation to Remote Physiological Measurement
by: Wang, Hao, et al.
Published: (2024) -
A Review of Predictive and Contrastive Self-supervised Learning for Medical Images
by: Wang, Wei-Chien, et al.
Published: (2023) -
A Dual-branch Self-supervised Representation Learning Framework for Tumour Segmentation in Whole Slide Images
by: Wang, Hao, et al.
Published: (2023)