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 are complicated by gestational diabetes mellitus (GDM). In addition, the increasing rate of obesity will likely rise the proportion of pregnancies complicated by both Type … Continued
Fourth MICCAI Workshop & Challenge on Spine Imaging In this workshop, we are inviting researchers to share and exchange their experience and expertise in spinal imaging and method development. Topics of interest include, but are not limited to: Clinical applications of spine imaging Computer-aided diagnosis of spine conditions Image-guided spine intervention and treatment … Continued
Understanding brain connectivity in a network-theoretic context has shown much promise in recent years. This type of analysis identifies brain organisational principles, bringing a new perspective to neuroscience. At the same time, large public databases of connectomic data are now available. However, connectome analysis is still an emerging field and there is a crucial need … Continued
This year we are co-organising the Workshop on Brain Analysis using Connectivity Networks at MICCAI’16 in Athens in the morning of Monday 17/10/2016. Please consider to submit your work until 10/06/2016! This workshop targets researchers for whom the effects of motion are critical in image analysis or visualisation. By inviting contributions across application areas we … 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 with additional shortcut-connections. The network is trained end-to-end from scratch with a very low number of annotated images per application. The surprisingly simple strategy to … 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 this overview presentation, I will touch upon several topics. Volumetric measures obtained via segmentation find their application in prenatal famine exposure, HIV and ischemic stroke. … 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, searching and locating objects of interest in images is a central problem in medical image computing. If anything, the need for efficient object detection techniques … 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 will discuss our innovation in network architecture to make our algorithms running real time on mobile devices as well as how we achieved a new … 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