Saved in:
| Main Authors: | Barekatain, Leili, Glocker, Ben |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2510.12021 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Average Calibration Losses for Reliable Uncertainty in Medical Image Segmentation
by: Barfoot, Theodore, et al.
Published: (2025)
by: Barfoot, Theodore, et al.
Published: (2025)
Pixel-level Counterfactual Contrastive Learning for Medical Image Segmentation
by: Lafargue-Hauret, Marceau, et al.
Published: (2026)
by: Lafargue-Hauret, Marceau, et al.
Published: (2026)
Distance Matters For Improving Performance Estimation Under Covariate Shift
by: Roschewitz, Mélanie, et al.
Published: (2023)
by: Roschewitz, Mélanie, et al.
Published: (2023)
Counterfactual Stress Testing for Image Classification Models
by: Stammel, Moritz, et al.
Published: (2026)
by: Stammel, Moritz, et al.
Published: (2026)
Identifiable Object Representations under Spatial Ambiguities
by: Kori, Avinash, et al.
Published: (2025)
by: Kori, Avinash, et al.
Published: (2025)
Demystifying Variational Diffusion Models
by: Ribeiro, Fabio De Sousa, et al.
Published: (2024)
by: Ribeiro, Fabio De Sousa, et al.
Published: (2024)
Explainable Transformer Prototypes for Medical Diagnoses
by: Demir, Ugur, et al.
Published: (2024)
by: Demir, Ugur, et al.
Published: (2024)
X-Edit: Exact, Explicit, and Explainable Null-Space Editing for Medical Vision Transformers
by: Liu, Yuanye, et al.
Published: (2026)
by: Liu, Yuanye, et al.
Published: (2026)
Average Calibration Error: A Differentiable Loss for Improved Reliability in Image Segmentation
by: Barfoot, Theodore, et al.
Published: (2024)
by: Barfoot, Theodore, et al.
Published: (2024)
Radio-opaque artefacts in digital mammography: automatic detection and analysis of downstream effects
by: Schueppert, Amelia, et al.
Published: (2024)
by: Schueppert, Amelia, et al.
Published: (2024)
Quantifying the Impact of Population Shift Across Age and Sex for Abdominal Organ Segmentation
by: Čevora, Kate, et al.
Published: (2024)
by: Čevora, Kate, et al.
Published: (2024)
Causal Representation Learning with Observational Grouping for CXR Classification
by: Rasal, Rajat, et al.
Published: (2025)
by: Rasal, Rajat, et al.
Published: (2025)
Hierarchical Vision Transformer with Prototypes for Interpretable Medical Image Classification
by: Gallée, Luisa, et al.
Published: (2025)
by: Gallée, Luisa, et al.
Published: (2025)
Improved EATFormer: A Vision Transformer for Medical Image Classification
by: Shisu, Yulong, et al.
Published: (2024)
by: Shisu, Yulong, et al.
Published: (2024)
Transparent Visual Reasoning via Object-Centric Agent Collaboration
by: Teoh, Benjamin, et al.
Published: (2025)
by: Teoh, Benjamin, et al.
Published: (2025)
Automatic dataset shift identification to support safe deployment of medical imaging AI
by: Roschewitz, Mélanie, et al.
Published: (2024)
by: Roschewitz, Mélanie, et al.
Published: (2024)
Federated Vision Transformer with Adaptive Focal Loss for Medical Image Classification
by: Zhao, Xinyuan, et al.
Published: (2026)
by: Zhao, Xinyuan, et al.
Published: (2026)
Combining imaging and shape features for prediction tasks of Alzheimer's disease classification and brain age regression
by: Shehata, Nairouz, et al.
Published: (2025)
by: Shehata, Nairouz, et al.
Published: (2025)
Decision-Aware Attention Propagation for Vision Transformer Explainability
by: Jo, Sehyeong, et al.
Published: (2026)
by: Jo, Sehyeong, et al.
Published: (2026)
MDViT: Multi-domain Vision Transformer for Small Medical Image Segmentation Datasets
by: Du, Siyi, et al.
Published: (2023)
by: Du, Siyi, et al.
Published: (2023)
Evaluating the Explainability of Attributes and Prototypes for a Medical Classification Model
by: Gallée, Luisa, et al.
Published: (2024)
by: Gallée, Luisa, et al.
Published: (2024)
TCSAFormer: Efficient Vision Transformer with Token Compression and Sparse Attention for Medical Image Segmentation
by: Xia, Zunhui, et al.
Published: (2025)
by: Xia, Zunhui, et al.
Published: (2025)
Embedding Radiomics into Vision Transformers for Multimodal Medical Image Classification
by: Yang, Zhenyu, et al.
Published: (2025)
by: Yang, Zhenyu, et al.
Published: (2025)
Where are we with calibration under dataset shift in image classification?
by: Roschewitz, Mélanie, et al.
Published: (2025)
by: Roschewitz, Mélanie, et al.
Published: (2025)
UNSURF: Uncertainty Quantification for Cortical Surface Reconstruction of Clinical Brain MRIs
by: Mehta, Raghav, et al.
Published: (2025)
by: Mehta, Raghav, et al.
Published: (2025)
Fine-tuning Vision Language Models with Graph-based Knowledge for Explainable Medical Image Analysis
by: Li, Chenjun, et al.
Published: (2025)
by: Li, Chenjun, et al.
Published: (2025)
Exploring the interplay of label bias with subgroup size and separability: A case study in mammographic density classification
by: Stanley, Emma A. M., et al.
Published: (2025)
by: Stanley, Emma A. M., et al.
Published: (2025)
ViConEx-Med: Visual Concept Explainability via Multi-Concept Token Transformer for Medical Image Analysis
by: Patrício, Cristiano, et al.
Published: (2025)
by: Patrício, Cristiano, et al.
Published: (2025)
Envisioning MedCLIP: A Deep Dive into Explainability for Medical Vision-Language Models
by: Hashmi, Anees Ur Rehman, et al.
Published: (2024)
by: Hashmi, Anees Ur Rehman, et al.
Published: (2024)
Medical Vision Generalist: Unifying Medical Imaging Tasks in Context
by: Ren, Sucheng, et al.
Published: (2024)
by: Ren, Sucheng, et al.
Published: (2024)
Training-free Test-time Improvement for Explainable Medical Image Classification
by: He, Hangzhou, et al.
Published: (2025)
by: He, Hangzhou, et al.
Published: (2025)
Is Grad-CAM Explainable in Medical Images?
by: Suara, Subhashis, et al.
Published: (2023)
by: Suara, Subhashis, et al.
Published: (2023)
ViTmiX: Vision Transformer Explainability Augmented by Mixed Visualization Methods
by: Hogea, Eduard, et al.
Published: (2024)
by: Hogea, Eduard, et al.
Published: (2024)
LeGrad: An Explainability Method for Vision Transformers via Feature Formation Sensitivity
by: Bousselham, Walid, et al.
Published: (2024)
by: Bousselham, Walid, et al.
Published: (2024)
FunnyNodules: A Customizable Medical Dataset Tailored for Evaluating Explainable AI
by: Gallée, Luisa, et al.
Published: (2025)
by: Gallée, Luisa, et al.
Published: (2025)
hZACH-ViT: Curved Latent Geometry for Compact Vision Transformers in Low-Data Medical Imaging
by: Angelakis, Athanasios
Published: (2026)
by: Angelakis, Athanasios
Published: (2026)
VLEER: Vision and Language Embeddings for Explainable Whole Slide Image Representation
by: Nguyen, Anh Tien, et al.
Published: (2025)
by: Nguyen, Anh Tien, et al.
Published: (2025)
Locality-Attending Vision Transformer
by: Hajimiri, Sina, et al.
Published: (2026)
by: Hajimiri, Sina, et al.
Published: (2026)
CBVLM: Training-free Explainable Concept-based Large Vision Language Models for Medical Image Classification
by: Patrício, Cristiano, et al.
Published: (2025)
by: Patrício, Cristiano, et al.
Published: (2025)
XAI-CLIP: ROI-Guided Perturbation Framework for Explainable Medical Image Segmentation in Multimodal Vision-Language Models
by: Alzubaidi, Thuraya, et al.
Published: (2026)
by: Alzubaidi, Thuraya, et al.
Published: (2026)
Similar Items
-
Average Calibration Losses for Reliable Uncertainty in Medical Image Segmentation
by: Barfoot, Theodore, et al.
Published: (2025) -
Pixel-level Counterfactual Contrastive Learning for Medical Image Segmentation
by: Lafargue-Hauret, Marceau, et al.
Published: (2026) -
Distance Matters For Improving Performance Estimation Under Covariate Shift
by: Roschewitz, Mélanie, et al.
Published: (2023) -
Counterfactual Stress Testing for Image Classification Models
by: Stammel, Moritz, et al.
Published: (2026) -
Identifiable Object Representations under Spatial Ambiguities
by: Kori, Avinash, et al.
Published: (2025)