Frontiers

Advanced AI for missing modality learning and uncertainty‑aware medical image analysis

Modern medical imaging increasingly relies on artificial intelligence to support detection, diagnosis, and prognostic ...
GitHub

I-MMSeg: Intensity-guided Multimodal Image Segmentation

[12/01/2025] The code for reproducing our multimodal myocardial pathology segmentation results on the MyoPS++ and MyoPS380 datasets is now available. This release is intended for peer review and ...
IEEE

Region Uncertainty Estimation for Medical Image Segmentation With Noisy Labels

Abstract: The success of deep learning in 3D medical image segmentation hinges on training with a large dataset of fully annotated 3D volumes, which are difficult and time-consuming to acquire.
GitHub

In-field 3D Reconstruction, Instance Segmentation and Phenotyping of Wheat Heads with Gaussian Splatting

Data used for Wheat3DGS and the baseline results for each plot (from 461 to 467) are structured as follows: Note that resolution is set to 1 to prevent image downscaling, and the training/test split ...
IEEE

Retrieval-Augmented Few-Shot Medical Image Segmentation With Foundation Models

Abstract: Medical image segmentation is crucial for clinical decision-making, but the scarcity of annotated data presents significant challenges. Few-shot segmentation (FSS) methods show promise but ...