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The ten dominant counter-narratives identified across Europe to Islamophobia and discussed in relation to national contexts are ranked and synthesised in this chapter. These in descending order of prevalence challenged constructions of Muslim ‘threat’, challenged exclusionary national projects, emphasised cultural compatibility and conviviality, elaborated Muslim plurality, challenged narratives of sexism, sought to build inclusive futures and deracialise the state, argued for Muslim normalisation, humanity and the creation of Muslim space(s) and challenged distorted representations of Muslims in the media and elsewhere.

The treatment of Muslims is the touchstone of contemporary European racism across its many nations and localities. We make a definitive case for two arguments in this book: firstly, the recognition of the accelerating and pervasive nature of Islamophobia in this region; and secondly, recognition that this process is being, can be, and will be challenged by counter-narratives that make the claim for Muslim humanity, plurality, space and justice. This book draws on new evidence from eight national contexts to provide an innovative kit of counter-narratives, which were presented and well received at the European Parliament in September 2018, and subsequently launched across Europe in national workshops in selected states. A synergy between leading academic researchers and the Islamic Human Rights Commission, Countering Islamophobia in Europe will be of value to EU institutions, governments and policy-makers, NGOs and media organisations, as well as researchers of multiculturalism, Islam, Muslims and immigration.

Law and Zakharov examine the formation and legacy of Russian racialisation and anti-Roma racism in a number of states including Hungary, the Czech Republic, Slovakia and Romania. They then examine racialisation in a variety of post-Soviet regimes including the Baltic states, Ukraine, Moldova, Belarus and the Southern Caucasus. The East European ‘search for race’ and the striving to ‘attain whiteness’, can be understood as attempts to rediscover the privileged whiteness that has been partly lost during the socialist past. Finally, they confirm the need to recognise polyracism, and give a less one-sided account of the process of racial Europeanisation which privileges Western Europe and denies the agency of Eastern European states in this process.

The incidence rate of all primary malignant and non-malignant brain and CNS tumours is 21 cases per 100,000. Gliomas are a broad term, which includes all tumours arising from glia and represents 30 % of all brain tumours and 80 % of all malignant brain tumours. Gliomas are the second leading cause of cancer mortality in people under the age of 35.

In this paper, we present a fully automated generative method for brain tumor segmentation in multi-modal magnetic resonance images. The method is based on the type of generative model often used for segmenting healthy brain tissues, where tissues are modeled by Gaussian mixture models combined with a spatial atlas-based tissue prior. We extend this basic model with a tumor prior, which uses convolutional restricted Boltzmann machines (cRBMs) to model the shape of both tumor core and complete tumor, which includes edema and core. The cRBMs are trained on expert segmentations of training images, without the use of the intensity information in the training images. Experiments on public benchmark data of patients suffering from low- and high-grade gliomas show that the method performs well compared to current state-of-the-art methods, while not being tied to any specific imaging protocol.