27 citations · 35 across the 5 of their papers we have counts for
5 papers
Dual-Domain Self-Supervised Learning for Accelerated Non-Cartesian MRI Reconstruction
Bo Zhou, Jo Schlemper, Neel Dey +5
While enabling accelerated acquisition and improved reconstruction accuracy, current deep MRI reconstruction networks are typically supervised, require fully sampled data, and are…
ContraReg: Contrastive Learning of Multi-modality Unsupervised Deformable Image Registration
Neel Dey, Jo Schlemper, Seyed Sadegh Mohseni Salehi +3
Establishing voxelwise semantic correspondence across distinct imaging modalities is a foundational yet formidable computer vision task. Current multi-modality registration techniq…
DSFormer: A Dual-domain Self-supervised Transformer for Accelerated Multi-contrast MRI Reconstruction
Bo Zhou, Neel Dey, Jo Schlemper +4
Multi-contrast MRI (MC-MRI) captures multiple complementary imaging modalities to aid in radiological decision-making. Given the need for lowering the time cost of multiple acquisi…
Straight to the point: reinforcement learning for user guidance in ultrasound
Fausto Milletari, Vighnesh Birodkar, Michal Sofka
Point of care ultrasound (POCUS) consists in the use of ultrasound imaging in critical or emergency situations to support clinical decisions by healthcare professionals and first r…
Learning detectors of malicious web requests for intrusion detection in network traffic
Lukas Machlica, Karel Bartos, Michal Sofka
This paper proposes a generic classification system designed to detect security threats based on the behavior of malware samples. The system relies on statistical features computed…