no code implementations • 10 Oct 2023 • Xiao Liu, Antanas Kascenas, Hannah Watson, Sotirios A. Tsaftaris, Alison Q. O'Neil
For brain tumour segmentation, deep learning models can achieve human expert-level performance given a large amount of data and pixel-level annotations.
no code implementations • 10 Oct 2023 • Joseph S. Boyle, Antanas Kascenas, Pat Lok, Maria Liakata, Alison Q. O'Neil
The task of assigning diagnostic ICD codes to patient hospital admissions is typically performed by expert human coders.
1 code implementation • 19 Jan 2023 • Antanas Kascenas, Pedro Sanchez, Patrick Schrempf, Chaoyang Wang, William Clackett, Shadia S. Mikhael, Jeremy P. Voisey, Keith Goatman, Alexander Weir, Nicolas Pugeault, Sotirios A. Tsaftaris, Alison Q. O'Neil
Denoising methods, for instance classical denoising autoencoders (DAEs) and more recently emerging diffusion models, are a promising approach, however naive application of pixelwise noise leads to poor anomaly detection performance.
1 code implementation • 25 Jul 2022 • Pedro Sanchez, Antanas Kascenas, Xiao Liu, Alison Q. O'Neil, Sotirios A. Tsaftaris
This requires training with healthy and unhealthy data in DPMs.
no code implementations • 14 May 2018 • Alison Q. O'Neil, Antanas Kascenas, Joseph Henry, Daniel Wyeth, Matthew Shepherd, Erin Beveridge, Lauren Clunie, Carrie Sansom, Evelina Šeduikytė, Keith Muir, Ian Poole
We present an efficient neural network method for locating anatomical landmarks in 3D medical CT scans, using atlas location autocontext in order to learn long-range spatial context.