1 code implementation • 17 Aug 2022 • Sam Ellis, Octavio E. Martinez Manzanera, Vasileios Baltatzis, Ibrahim Nawaz, Arjun Nair, Loïc le Folgoc, Sujal Desai, Ben Glocker, Julia A. Schnabel
This makes high-quality GANs useful for unsupervised anomaly detection in medical imaging.
no code implementations • 8 Oct 2021 • Loic Le Folgoc, Vasileios Baltatzis, Sujal Desai, Anand Devaraj, Sam Ellis, Octavio E. Martinez Manzanera, Arjun Nair, Huaqi Qiu, Julia Schnabel, Ben Glocker
We question the properties of MC Dropout for approximate inference, as in fact MC Dropout changes the Bayesian model; its predictive posterior assigns $0$ probability to the true model on closed-form benchmarks; the multimodality of its predictive posterior is not a property of the true predictive posterior but a design artefact.
no code implementations • 11 Aug 2021 • Vasileios Baltatzis, Kyriaki-Margarita Bintsi, Loic Le Folgoc, Octavio E. Martinez Manzanera, Sam Ellis, Arjun Nair, Sujal Desai, Ben Glocker, Julia A. Schnabel
Using publicly available data to determine the performance of methodological contributions is important as it facilitates reproducibility and allows scrutiny of the published results.
no code implementations • 10 Aug 2021 • Vasileios Baltatzis, Loic Le Folgoc, Sam Ellis, Octavio E. Martinez Manzanera, Kyriaki-Margarita Bintsi, Arjun Nair, Sujal Desai, Ben Glocker, Julia A. Schnabel
Convolutional Neural Networks (CNNs) are widely used for image classification in a variety of fields, including medical imaging.
no code implementations • 31 Jul 2021 • Loic Le Folgoc, Vasileios Baltatzis, Amir Alansary, Sujal Desai, Anand Devaraj, Sam Ellis, Octavio E. Martinez Manzanera, Fahdi Kanavati, Arjun Nair, Julia Schnabel, Ben Glocker
This mismatch is known as sampling bias.