Publications (59)
BioX-CPath: Biologically-driven Explainable Diagnostics for Multistain IHC Computational Pathology
Amaya Gallagher-Syed, Henry Senior, Omnia Alwazzan +7
The development of biologically interpretable and explainable models remains a key challenge in computational pathology, particularly for multistain immunohistochemistry (IHC) anal…
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…
MOAB: Multi-Modal Outer Arithmetic Block For Fusion Of Histopathological Images And Genetic Data For Brain Tumor Grading
Omnia Alwazzan, Abbas Khan, Ioannis Patras +1
Brain tumors are an abnormal growth of cells in the brain. They can be classified into distinct grades based on their growth. Often grading is performed based on a histological ima…
DeepLPF: Deep Local Parametric Filters for Image Enhancement
Sean Moran, Pierre Marza, Steven McDonagh +2
Digital artists often improve the aesthetic quality of digital photographs through manual retouching. Beyond global adjustments, professional image editing programs provide local a…
FlexHDR: Modelling Alignment and Exposure Uncertainties for Flexible HDR Imaging
Sibi Catley-Chandar, Thomas Tanay, Lucas Vandroux +3
High dynamic range (HDR) imaging is of fundamental importance in modern digital photography pipelines and used to produce a high-quality photograph with well exposed regions despit…
FOAA: Flattened Outer Arithmetic Attention For Multimodal Tumor Classification
Omnia Alwazzan, Ioannis Patras, Gregory Slabaugh
Fusion of multimodal healthcare data holds great promise to provide a holistic view of a patient's health, taking advantage of the complementarity of different modalities while lev…