Giant prolactinomas: Multi-modal approach to achieve tumor control

A Multi - Modal Approach to Functional Neuroimaging

The work undertaken involves the use of functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) as separate but complementary non-invasive functional brain imaging modalities. The aim in combining fMRI and MEG is centred around exploitation of the high temporal resolution available in MEG, and the high spatial resolution available in fMRI. However, whilst MEG represents a ...

Multi-Modal Control: From Motion Description Languages to Optimal Control

Learning Multi-modal Control Programs

Multi-modal control is a commonly used design tool for breaking up complex control tasks into sequences of simpler tasks. In this paper, we show that by viewing the control space as a set of such tokenized instructions rather than as real-valued signals, reinforcement learning becomes applicable to continuous-time control systems. In fact, we show how a combination of state-space exploration an...

ilastik for Multi-modal Brain Tumor Segmentation

We present the application of ilastik, the open source interactive learning and segmentation toolkit, for brain tumor segmentation in multi-modal magnetic resonance images. Even without utilizing the interactive nature of the toolkit, we are able to achieve Dice scores comparable to human inter-rater variability and are ranked in the top-5 results for the BraTS 2013 challenge data set, where no...

A local approach to modal logic for multi - agentsystems ?