Saved in:
| Main Authors: | Bergström, Herman, Yue, Zhongqi, Johansson, Fredrik D. |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2510.24385 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Letter to the Editor: What are the legal and ethical considerations of submitting radiology reports to ChatGPT?
by: Agarwal, Siddharth, et al.
Published: (2024)
by: Agarwal, Siddharth, et al.
Published: (2024)
More performant and scalable: Rethinking contrastive vision-language pre-training of radiology in the LLM era
by: Li, Yingtai, et al.
Published: (2025)
by: Li, Yingtai, et al.
Published: (2025)
Scaling medical imaging report generation with multimodal reinforcement learning
by: Liu, Qianchu, et al.
Published: (2026)
by: Liu, Qianchu, et al.
Published: (2026)
RAPS-3D: Efficient interactive segmentation for 3D radiological imaging
by: Danielou, Théo, et al.
Published: (2025)
by: Danielou, Théo, et al.
Published: (2025)
Comprehensive language-image pre-training for 3D medical image understanding
by: Wald, Tassilo, et al.
Published: (2025)
by: Wald, Tassilo, et al.
Published: (2025)
Leveraging generative models to characterize the failure conditions of image classifiers
by: LeCoz, Adrien, et al.
Published: (2024)
by: LeCoz, Adrien, et al.
Published: (2024)
MAIRA-1: A specialised large multimodal model for radiology report generation
by: Hyland, Stephanie L., et al.
Published: (2023)
by: Hyland, Stephanie L., et al.
Published: (2023)
DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder
by: He, Dan, et al.
Published: (2025)
by: He, Dan, et al.
Published: (2025)
Semi-weakly-supervised neural network training for medical image registration
by: Li, Yiwen, et al.
Published: (2024)
by: Li, Yiwen, et al.
Published: (2024)
Anatomical grounding pre-training for medical phrase grounding
by: Zhang, Wenjun, et al.
Published: (2025)
by: Zhang, Wenjun, et al.
Published: (2025)
Few-shot Learner Parameterization by Diffusion Time-steps
by: Yue, Zhongqi, et al.
Published: (2024)
by: Yue, Zhongqi, et al.
Published: (2024)
DeViDe: Faceted medical knowledge for improved medical vision-language pre-training
by: Luo, Haozhe, et al.
Published: (2024)
by: Luo, Haozhe, et al.
Published: (2024)
Can language-guided unsupervised adaptation improve medical image classification using unpaired images and texts?
by: Rahman, Umaima, et al.
Published: (2024)
by: Rahman, Umaima, et al.
Published: (2024)
The effects of using created synthetic images in computer vision training
by: Smutny, John W.
Published: (2025)
by: Smutny, John W.
Published: (2025)
Revisiting MAE pre-training for 3D medical image segmentation
by: Wald, Tassilo, et al.
Published: (2024)
by: Wald, Tassilo, et al.
Published: (2024)
In-context learning enables multimodal large language models to classify cancer pathology images
by: Ferber, Dyke, et al.
Published: (2024)
by: Ferber, Dyke, et al.
Published: (2024)
On dataset transferability in medical image classification
by: Juodelyte, Dovile, et al.
Published: (2024)
by: Juodelyte, Dovile, et al.
Published: (2024)
Exploring connections of spectral analysis and transfer learning in medical imaging
by: Lu, Yucheng, et al.
Published: (2024)
by: Lu, Yucheng, et al.
Published: (2024)
Thinking with Images as Continuous Actions: Numerical Visual Chain-of-Thought
by: Zhao, Kesen, et al.
Published: (2026)
by: Zhao, Kesen, et al.
Published: (2026)
INSITE: labelling medical images using submodular functions and semi-supervised data programming
by: Gautam, Akshat, et al.
Published: (2024)
by: Gautam, Akshat, et al.
Published: (2024)
MOSMOS: Multi-organ segmentation facilitated by medical report supervision
by: Tian, Weiwei, et al.
Published: (2024)
by: Tian, Weiwei, et al.
Published: (2024)
GreenRFM: Toward a resource-efficient radiology foundation model
by: Li, Yingtai, et al.
Published: (2026)
by: Li, Yingtai, et al.
Published: (2026)
CXR-Agent: Vision-language models for chest X-ray interpretation with uncertainty aware radiology reporting
by: Sharma, Naman
Published: (2024)
by: Sharma, Naman
Published: (2024)
Understanding differences in applying DETR to natural and medical images
by: Xu, Yanqi, et al.
Published: (2024)
by: Xu, Yanqi, et al.
Published: (2024)
Net2Net: When Un-trained Meets Pre-trained Networks for Robust Real-World Denoising
by: Yuan, Weimin, et al.
Published: (2025)
by: Yuan, Weimin, et al.
Published: (2025)
Plug-and-Play Algorithm Convergence Analysis From The Standpoint of Stochastic Differential Equation
by: Wang, Zhongqi, et al.
Published: (2024)
by: Wang, Zhongqi, et al.
Published: (2024)
Exploring Diffusion Time-steps for Unsupervised Representation Learning
by: Yue, Zhongqi, et al.
Published: (2024)
by: Yue, Zhongqi, et al.
Published: (2024)
Automatic Report Generation for Histopathology images using pre-trained Vision Transformers and BERT
by: Sengupta, Saurav, et al.
Published: (2023)
by: Sengupta, Saurav, et al.
Published: (2023)
Trainwreck: A damaging adversarial attack on image classifiers
by: Zahálka, Jan
Published: (2023)
by: Zahálka, Jan
Published: (2023)
Expert-level vision-language foundation model for real-world radiology and comprehensive evaluation
by: Liu, Xiaohong, et al.
Published: (2024)
by: Liu, Xiaohong, et al.
Published: (2024)
Dynamic Attention Analysis for Backdoor Detection in Text-to-Image Diffusion Models
by: Wang, Zhongqi, et al.
Published: (2025)
by: Wang, Zhongqi, et al.
Published: (2025)
Assimilation Matters: Model-level Backdoor Detection in Vision-Language Pretrained Models
by: Wang, Zhongqi, et al.
Published: (2025)
by: Wang, Zhongqi, et al.
Published: (2025)
T2IShield: Defending Against Backdoors on Text-to-Image Diffusion Models
by: Wang, Zhongqi, et al.
Published: (2024)
by: Wang, Zhongqi, et al.
Published: (2024)
Bridging spatial awareness and global context in medical image segmentation
by: Alzu'bi, Dalia, et al.
Published: (2025)
by: Alzu'bi, Dalia, et al.
Published: (2025)
Deep classification algorithm for De-identification of DICOM medical images
by: Michele, Bufano, et al.
Published: (2025)
by: Michele, Bufano, et al.
Published: (2025)
Prompt learning with bounding box constraints for medical image segmentation
by: Gaillochet, Mélanie, et al.
Published: (2025)
by: Gaillochet, Mélanie, et al.
Published: (2025)
Exploring scalable medical image encoders beyond text supervision
by: Pérez-García, Fernando, et al.
Published: (2024)
by: Pérez-García, Fernando, et al.
Published: (2024)
Impact of domain adaptation in deep learning for medical image classifications
by: Wu, Yihang, et al.
Published: (2026)
by: Wu, Yihang, et al.
Published: (2026)
Mask of truth: model sensitivity to unexpected regions of medical images
by: Sourget, Théo, et al.
Published: (2024)
by: Sourget, Théo, et al.
Published: (2024)
A hybrid Kolmogorov-Arnold network for medical image segmentation
by: Bhattacharyya, Deep, et al.
Published: (2026)
by: Bhattacharyya, Deep, et al.
Published: (2026)
Similar Items
-
Letter to the Editor: What are the legal and ethical considerations of submitting radiology reports to ChatGPT?
by: Agarwal, Siddharth, et al.
Published: (2024) -
More performant and scalable: Rethinking contrastive vision-language pre-training of radiology in the LLM era
by: Li, Yingtai, et al.
Published: (2025) -
Scaling medical imaging report generation with multimodal reinforcement learning
by: Liu, Qianchu, et al.
Published: (2026) -
RAPS-3D: Efficient interactive segmentation for 3D radiological imaging
by: Danielou, Théo, et al.
Published: (2025) -
Comprehensive language-image pre-training for 3D medical image understanding
by: Wald, Tassilo, et al.
Published: (2025)