42 citations · 56 across the 5 of their papers we have counts for
5 papers
Low-field magnetic resonance image enhancement via stochastic image quality transfer
Hongxiang Lin, Matteo Figini, Felice D'Arco +10
Low-field (<1T) magnetic resonance imaging (MRI) scanners remain in widespread use in low- and middle-income countries (LMICs) and are commonly used for some applications in higher…
Image Quality Transfer Enhances Contrast and Resolution of Low-Field Brain MRI in African Paediatric Epilepsy Patients
Matteo Figini, Hongxiang Lin, Godwin Ogbole +10
1.5T or 3T scanners are the current standard for clinical MRI, but low-field (<1T) scanners are still common in many lower- and middle-income countries for reasons of cost and robu…
Deep Learning for Low-Field to High-Field MR: Image Quality Transfer with Probabilistic Decimation Simulator
Hongxiang Lin, Matteo Figini, Ryutaro Tanno +10
MR images scanned at low magnetic field (T) have lower resolution in the slice direction and lower contrast, due to a relatively small signal-to-noise ratio (SNR) than those fr…
Data-Driven Malaria Prevalence Prediction in Large Densely-Populated Urban Holoendemic sub-Saharan West Africa: Harnessing Machine Learning Approaches and 22-years of Prospectively Collected Data
Biobele J. Brown, Alexander A. Przybylski, Petru Manescu +20
Plasmodium falciparum malaria still poses one of the greatest threats to human life with over 200 million cases globally leading to half-million deaths annually. Of these, 90% of c…
Deep Learning Enhanced Extended Depth-of-Field for Thick Blood-Film Malaria High-Throughput Microscopy
Petru Manescu, Lydia Neary- Zajiczek, Michael J. Shaw +10
Fast accurate diagnosis of malaria is still a global health challenge for which automated digital-pathology approaches could provide scalable solutions amenable to be deployed in l…