1 citations · 1 across the 10 of their papers we have counts for
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Compositional Segmentation of Cardiac Images Leveraging Metadata
Abbas Khan, Muhammad Asad, Martin Benning +2
Cardiac image segmentation is essential for automated cardiac function assessment and monitoring of changes in cardiac structures over time. Inspired by coarse-to-fine approaches i…
Improving Interpretability and Robustness for the Detection of AI-Generated Images
Tatiana Gaintseva, Laida Kushnareva, German Magai +5
With growing abilities of generative models, artificial content detection becomes an increasingly important and difficult task. However, all popular approaches to this problem suff…
CAMS: Convolution and Attention-Free Mamba-based Cardiac Image Segmentation
Abbas Khan, Muhammad Asad, Martin Benning +2
Convolutional Neural Networks (CNNs) and Transformer-based self-attention models have become the standard for medical image segmentation. This paper demonstrates that convolution a…
Multi-view Cardiac Image Segmentation via Trans-Dimensional Priors
Abbas Khan, Muhammad Asad, Martin Benning +2
We propose a novel multi-stage trans-dimensional architecture for multi-view cardiac image segmentation. Our method exploits the relationship between long-axis (2D) and short-axis…
RAVE: Residual Vector Embedding for CLIP-Guided Backlit Image Enhancement
Tatiana Gaintseva, Martin Benning, Gregory Slabaugh
In this paper we propose a novel modification of Contrastive Language-Image Pre-Training (CLIP) guidance for the task of unsupervised backlit image enhancement. Our work builds on…
Crop and Couple: cardiac image segmentation using interlinked specialist networks
Abbas Khan, Muhammad Asad, Martin Benning +2
Diagnosis of cardiovascular disease using automated methods often relies on the critical task of cardiac image segmentation. We propose a novel strategy that performs segmentation…