2 citations · 2 across the 4 of their papers we have counts for
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Are Natural-Domain Foundation Models Effective for Accelerated Cardiac MRI Reconstruction?
Anam Hashmi, Mayug Maniparambil, Julia Dietlmeier +2
The emergence of large-scale pretrained foundation models has transformed computer vision, enabling strong performance across diverse downstream tasks. However, their potential for…
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…
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…
Accelerating Cardiac MRI Reconstruction with CMRatt: An Attention-Driven Approach
Anam Hashmi, Julia Dietlmeier, Kathleen M. Curran +1
Cine cardiac magnetic resonance (CMR) imaging is recognised as the benchmark modality for the comprehensive assessment of cardiac function. Nevertheless, the acquisition process of…