Sally Collins
Professor of Obstetrics, University of Oxford / Perspectum
About me
About
Sally is a Professor of Obstetrics at the University of Oxford and the Medical Lead for Women’s health for Perspectum Ltd.
Sally graduated in Medicine from the University of Oxford and specialized in Obstetrics and Gynaecology, training within the Oxford region during which time she completed a PhD in Obstetric Ultrasound which started her journey in AI for medical imaging.
She is highly research active having authored over 100 journal articles, filed three patents and won several international research awards.
Using machine learning techniques her team pioneered the first fully automated method for estimating placental morphology and vascularity from a 3D-PD ultrasound image, the OxNNet Toolkit. In collaboration with Perspectum Ltd, she is PI on a Phase 2 grant from the NIHR AI in Health and Care awards. This aims to test the clinical utility of the OxNNet Toolkit to predict adverse pregnancy outcomes from a simple first trimester ultrasound scan. A second study is also underway to investigate how easily it can be embedded into a standard NHS ultrasound department and provide a full healthcare economic analysis. It is hoped that this will form the basis of a multifactorial, early pregnancy screening test for fetal growth restriction and pre-eclampsia.
Using transfer learning her team are now applying their fully convolutional neural network to assess the volume and vascularity of other organs and tumours.
Sally graduated in Medicine from the University of Oxford and specialized in Obstetrics and Gynaecology, training within the Oxford region during which time she completed a PhD in Obstetric Ultrasound which started her journey in AI for medical imaging.
She is highly research active having authored over 100 journal articles, filed three patents and won several international research awards.
Using machine learning techniques her team pioneered the first fully automated method for estimating placental morphology and vascularity from a 3D-PD ultrasound image, the OxNNet Toolkit. In collaboration with Perspectum Ltd, she is PI on a Phase 2 grant from the NIHR AI in Health and Care awards. This aims to test the clinical utility of the OxNNet Toolkit to predict adverse pregnancy outcomes from a simple first trimester ultrasound scan. A second study is also underway to investigate how easily it can be embedded into a standard NHS ultrasound department and provide a full healthcare economic analysis. It is hoped that this will form the basis of a multifactorial, early pregnancy screening test for fetal growth restriction and pre-eclampsia.
Using transfer learning her team are now applying their fully convolutional neural network to assess the volume and vascularity of other organs and tumours.
Matchmaking Information
Loading...