28 citations · 54 across the 9 of their papers we have counts for
18 papers
CAS-Net: Conditional Atlas Generation and Brain Segmentation for Fetal MRI
Liu Li, Qiang Ma, Matthew Sinclair +6
Fetal Magnetic Resonance Imaging (MRI) is used in prenatal diagnosis and to assess early brain development. Accurate segmentation of the different brain tissues is a vital step in…
Split HE: Fast Secure Inference Combining Split Learning and Homomorphic Encryption
George-Liviu Pereteanu, Amir Alansary, Jonathan Passerat-Palmbach
This work presents a novel protocol for fast secure inference of neural networks applied to computer vision applications. It focuses on improving the overall performance of the onl…
PialNN: A Fast Deep Learning Framework for Cortical Pial Surface Reconstruction
Qiang Ma, Emma C. Robinson, Bernhard Kainz +2
Traditional cortical surface reconstruction is time consuming and limited by the resolution of brain Magnetic Resonance Imaging (MRI). In this work, we introduce Pial Neural Networ…
Bayesian analysis of the prevalence bias: learning and predicting from imbalanced data
Loic Le Folgoc, Vasileios Baltatzis, Amir Alansary +8
Datasets are rarely a realistic approximation of the target population. Say, prevalence is misrepresented, image quality is above clinical standards, etc. This mismatch is known as…
Communicative Reinforcement Learning Agents for Landmark Detection in Brain Images
Guy Leroy, Daniel Rueckert, Amir Alansary
Accurate detection of anatomical landmarks is an essential step in several medical imaging tasks. We propose a novel communicative multi-agent reinforcement learning (C-MARL) syste…
Geometric Deep Learning for Post-Menstrual Age Prediction based on the Neonatal White Matter Cortical Surface
Vitalis Vosylius, Andy Wang, Cemlyn Waters +8
Accurate estimation of the age in neonates is essential for measuring neurodevelopmental, medical, and growth outcomes. In this paper, we propose a novel approach to predict the po…