13 citations · 34 across the 8 of their papers we have counts for
8 papers
Vector Quantisation for Robust Segmentation
Ainkaran Santhirasekaram, Avinash Kori, Mathias Winkler +2
The reliability of segmentation models in the medical domain depends on the model's robustness to perturbations in the input space. Robustness is a particular challenge in medical…
Hierarchical Symbolic Reasoning in Hyperbolic Space for Deep Discriminative Models
Ainkaran Santhirasekaram, Avinash Kori, Andrea Rockall +3
Explanations for \emph{black-box} models help us understand model decisions as well as provide information on model biases and inconsistencies. Most of the current explainability t…
Multiple Instance Learning with Auxiliary Task Weighting for Multiple Myeloma Classification
Talha Qaiser, Stefan Winzeck, Theodore Barfoot +9
Whole body magnetic resonance imaging (WB-MRI) is the recommended modality for diagnosis of multiple myeloma (MM). WB-MRI is used to detect sites of disease across the entire skele…
Fully-automated deep learning slice-based muscle estimation from CT images for sarcopenia assessment
Fahdi Kanavati, Shah Islam, Zohaib Arain +2
Objective: To demonstrate the effectiveness of using a deep learning-based approach for a fully automated slice-based measurement of muscle mass for assessing sarcopenia on CT scan…
Automatic L3 slice detection in 3D CT images using fully-convolutional networks
Fahdi Kanavati, Shah Islam, Eric O. Aboagye +1
The analysis of single CT slices extracted at the third lumbar vertebra (L3) has garnered significant clinical interest in the past few years, in particular in regards to quantifyi…
Small Organ Segmentation in Whole-body MRI using a Two-stage FCN and Weighting Schemes
Vanya V. Valindria, Ioannis Lavdas, Juan Cerrolaza +4
Accurate and robust segmentation of small organs in whole-body MRI is difficult due to anatomical variation and class imbalance. Recent deep network based approaches have demonstra…