19 citations · 24 across the 9 of their papers we have counts for
13 papers
Uncertainty-Guided Handshake: Efficient Human-in-the-Loop Refinement for Surgical-Grade Glioma Segmentation
Samuel Hart, Ahmad Yahya, Ahmed Karam Eldaly
While state-of-the-art automated models for medical image segmentation achieve high mean performance, they frequently suffer from localized, catastrophic failures that preclude saf…
Trustworthy MRI Reconstruction via Bayesian Uncertainty Quantification with Sparsity Prior Models
Ahmed Karam Eldaly, Matteo Figini, Daniel C. Alexander
We propose a novel Bayesian framework for joint image reconstruction and uncertainty quantification from compressed sensing magnetic resonance imaging data. The problem is formulat…
Low-Field Magnetic Resonance Image Enhancement using Undersampled k-Space
Daniel Tweneboah Anyimadu, Mohammed Abdalla, Mohammed M. Abdelsamea +1
Low-field magnetic resonance imaging (MRI) offers a cost-effective alternative for medical imaging in resource-limited settings. However, its widespread adoption is hindered by two…
Low-Field Magnetic Resonance Image Quality Enhancement using Undersampled k-Space and Out-of-Distribution Generalisation
Daniel Tweneboah Anyimadu, Mohammed M. Abdelsamea, Ahmed Karam Eldaly
Low-field magnetic resonance imaging (MRI) offers affordable access to diagnostic imaging but faces challenges such as prolonged acquisition times and reduced image quality. Althou…
Bayesian Uncertainty-Aware MRI Reconstruction
Ahmed Karam Eldaly, Matteo Figini, Daniel C. Alexander
We propose a novel framework for joint magnetic resonance image reconstruction and uncertainty quantification using under-sampled k-space measurements. The problem is formulated as…
DeepHistoViT: An Interpretable Vision Transformer Framework for Histopathological Cancer Classification
Ravi Mosalpuri, Mohammed Abdelsamea, Ahmed Karam Eldaly
Histopathology remains the gold standard for cancer diagnosis because it provides detailed cellular-level assessment of tissue morphology. However, manual histopathological examina…
Causal Transfer in Medical Image Analysis
Mohammed M. Abdelsamea, Daniel Tweneboah Anyimadu, Tasneem Selim +4
Medical imaging models frequently fail when deployed across hospitals, scanners, populations, or imaging protocols due to domain shift, limiting their clinical reliability. While t…
Direct low-field MRI super-resolution using undersampled k-space
Daniel Tweneboah Anyimadu, Mohammed M. Abdelsamea, Ahmed Karam Eldaly
Low-field magnetic resonance imaging (MRI) provides affordable access to diagnostic imaging but suffers from prolonged acquisition and limited image quality. Accelerated imaging ca…
Low-Field Magnetic Resonance Image Quality Enhancement using a Conditional Flow Matching Model
Huu Tien Nguyen, Ahmed Karam Eldaly
This paper introduces a novel framework for image quality transfer based on conditional flow matching (CFM). Unlike conventional generative models that rely on iterative sampling o…
Alternative Learning Paradigms for Image Quality Transfer
Ahmed Karam Eldaly, Matteo Figini, Daniel C. Alexander
Image Quality Transfer (IQT) aims to enhance the contrast and resolution of low-quality medical images, e.g. obtained from low-power devices, with rich information learned from hig…
A 3D Conditional Diffusion Model for Image Quality Transfer -- An Application to Low-Field MRI
Seunghoi Kim, Henry F. J. Tregidgo, Ahmed K. Eldaly +2
Low-field (LF) MRI scanners (<1T) are still prevalent in settings with limited resources or unreliable power supply. However, they often yield images with lower spatial resolution…
Patch-Based Sparse Representation For Bacterial Detection
Ahmed Karam Eldaly, Yoann Altmann, Ahsan Akram +3
In this paper, we propose an unsupervised approach for bacterial detection in optical endomicroscopy images. This approach splits each image into a set of overlapping patches and a…
Deconvolution and Restoration of Optical Endomicroscopy Images
Ahmed Karam Eldaly, Yoann Altmann, Antonios Perperidis +4
Optical endomicroscopy (OEM) is an emerging technology platform with preclinical and clinical imaging applications. Pulmonary OEM via fibre bundles has the potential to provide in…