2 citations · 2 across the 1 of their papers we have counts for
6 papers
Towards Investigating Residual Hearing Loss: Quantification of Fibrosis in a Novel Cochlear OCT Dataset
Julia Dietlmeier, Benjamin Greenberg, Wenxuan He +10
Objective: Cochlear implants (CIs) are bionic prostheses that restores hearing via electrical stimulation of the auditory nerve. Hybrid CIs, which use electroacoustic stimulation (…
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…
Cross-Modal Knowledge Distillation for PET-Free Amyloid-Beta Detection from MRI
Francesco Chiumento, Julia Dietlmeier, Ronan P. Killeen +3
Detecting amyloid- (A) positivity is crucial for early diagnosis of Alzheimer's disease but typically requires PET imaging, which is costly, invasive, and not widely access…
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…
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…