Sandy Wells is giving a talk on Wednesday 16 Dec, 11:00, in Huxley 218. He will be talking about his registration work and will give an overview of projects in … Continued

Title: Graph-based deformable registration: slice-to-volume mapping and context specific methods Abstract: Image registration methods, which aim at aligning two or more images into one coordinate system, are among the oldest … Continued

Title: The challenges of developing an active deep-learning platform Abstract: Deep learning is usually linked to Big Data. However, there are several scientific, engineering and medical imaging problems with limited … Continued

Personalized Blood Flow Simulation from an Image-Derived Model: Changing the Paradigm for Cardiovascular Diagnostics Abstract: Coronary heart disease is the leading cause of mortality worldwide, accounting for 1/3 of all … Continued

Improving clinical application of cardiac diffusion tensor MRI Abstract  Magnetic resonance diffusion tensor imaging (MRDTI), also known as DTI, has emerged as a powerful non-invasive tool for mapping the orientation-dependent microanatomical … Continued

Quantitative Ultrasound Imaging for Diagnosis and Intervention: A Machine Learning Approach Abstract: In recent years, quantitative ultrasound has emerged as a promising technology to improve diagnosis, increase the precision of interventions, … Continued

Segmenting 2D+T ultrasound imaging data in fetus: improving the estimation of biomarkers of risky adaptations Abstract: Approximately 10% of the pregnancies are complicated by growth restriction and 7% of pregnancies … Continued

U-net: Convolutional Networks for Biomedical Image Segmentation Abstract: In this talk I will present our u-net for biomedical image segmentation. The architecture consists of an analysis path and a synthesis path … Continued

Quantifying MRI: from reconstruction to application in neuroimaging Abstract: To understand the origin and development of neurological disorders, Magnetic Resonance Imaging (MRI) has proven to provide valuable quantitative measures. In … Continued

Title: Learning structure in complex data: machine learning for medical image segmentation, registration and shape analysis