3 papers
cs.CV2025
Towards Label-Free Brain Tumor Segmentation: Unsupervised Learning with Multimodal MRI
Gerard Comas-Quiles, Carles Garcia-Cabrera, Julia Dietlmeier +2
Unsupervised anomaly detection (UAD) presents a complementary alternative to supervised learning for brain tumor segmentation in magnetic resonance imaging (MRI), particularly when…
eess.IV2025
VLSM-Ensemble: Ensembling CLIP-based Vision-Language Models for Enhanced Medical Image Segmentation
Julia Dietlmeier, Oluwabukola Grace Adegboro, Vayangi Ganepola +2
Vision-language models and their adaptations to image segmentation tasks present enormous potential for producing highly accurate and interpretable results. However, implementation…
eess.IV2025
Parameter-Free Bio-Inspired Channel Attention for Enhanced Cardiac MRI Reconstruction
Anam Hashmi, Julia Dietlmeier, Kathleen M. Curran +1
Attention is a fundamental component of the human visual recognition system. The inclusion of attention in a convolutional neural network amplifies relevant visual features and sup…