74 citations · 302 across the 26 of their papers we have counts for
32 papers · 1 filter
A Comparative Study of Graph Neural Networks for Shape Classification in Neuroimaging
Nairouz Shehata, Wulfie Bain, Ben Glocker
Graph neural networks have emerged as a promising approach for the analysis of non-Euclidean data such as meshes. In medical imaging, mesh-like data plays an important role for mod…
Frequency Dropout: Feature-Level Regularization via Randomized Filtering
Mobarakol Islam, Ben Glocker
Deep convolutional neural networks have shown remarkable performance on various computer vision tasks, and yet, they are susceptible to picking up spurious correlations from the tr…
Uncertainty quantification in non-rigid image registration via stochastic gradient Markov chain Monte Carlo
Daniel Grzech, Mohammad Farid Azampour, Huaqi Qiu +3
We develop a new Bayesian model for non-rigid registration of three-dimensional medical images, with a focus on uncertainty quantification. Probabilistic registration of large imag…
Class-Distribution-Aware Calibration for Long-Tailed Visual Recognition
Mobarakol Islam, Lalithkumar Seenivasan, Hongliang Ren +1
Despite impressive accuracy, deep neural networks are often miscalibrated and tend to overly confident predictions. Recent techniques like temperature scaling (TS) and label smooth…
The Pitfalls of Sample Selection: A Case Study on Lung Nodule Classification
Vasileios Baltatzis, Kyriaki-Margarita Bintsi, Loic Le Folgoc +6
Using publicly available data to determine the performance of methodological contributions is important as it facilitates reproducibility and allows scrutiny of the published resul…
The Effect of the Loss on Generalization: Empirical Study on Synthetic Lung Nodule Data
Vasileios Baltatzis, Loic Le Folgoc, Sam Ellis +6
Convolutional Neural Networks (CNNs) are widely used for image classification in a variety of fields, including medical imaging. While most studies deploy cross-entropy as the loss…