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
Finding the needle in the haystack: detection, tracking and registration in biomedical imaging Abstract From centimeter-sized observations visible in endoscopy to nanometer large intra-cellular structures discernible with Electron Microscopes, … Continued
Neural network's for super resolution Abstract The most important parts for using neural network's for super resolution are data, network architecture and the objective functions. In this talk we … Continued
Title: Learning structure in complex data: machine learning for medical image segmentation, registration and shape analysis
Title: MRI of placenta: from pixels to function