Learning-based Algorithms for Inverse Problems in MR Image Reconstruction and Quantitative Perfusion Imaging

Medical imaging has become an integral part of the clinical pipeline through its widespread use in the diagnosis, prognosis and treatment planning of several diseases. Magnetic Resonance Imaging (MRI) is particularly useful because it is free from ionizing radiation and is able to provide excellent soft tissue contrast. However, MRI suffers from drawbacks like long scanning durations that increase the cost of imaging and render the acquired images vulnerable to artifacts like motion. In modalities like Arterial Spin Labeling (ASL), which is used for non-invasive and quantitative perfusion imaging, low signal-to-noise ratio and lack of precision in parameter estimates also present significant problems. In this thesis, we develop and present algorithms whose focus can be divided into two broad categories. First, we investigate the reconstruction of MR images from fewer measurements, using data-driven machine learning to fill in the gaps in acquisition, thereby reducing the scan duration. Specifically, we first combine a supervised and an unsupervised (blind) learned dictionary in a residual fashion as a spatial prior in MR image reconstruction, and then extend this framework to include deep supervised learning. The latter, called blind primed supervised (BLIPS) learning, proposes that there exists synergy between features learned using shallower dictionary-based methods or traditional prior-based image reconstruction and those learned using newer deep supervised learning-based approaches. We show that this synergy can be exploited to yield reconstructions that are approx. 0.5-1 dB better in PSNR (in avg. across undersampling patterns). We also observe that the BLIPS algorithm is more robust to a scarcity of available training data, yielding reconstructions that are approx. 0.8 dB better (in terms of avg. PSNR) compared to strict supervised learning reconstruction when training data is very limited. Secondly, we aim to provide more precise estimates for multiple physiological parameters and tissue properties from ASL scans by estimation-theory-based optimization of ASL scan design, and combination with MR Fingerprinting. For this purpose, we use the Cramer-Rao Lower Bound (CRLB) for optimizing the scan design, and deep learning for regression-based estimation. We also show that regardless of the estimator used, optimization improves the precision in parameter estimates, and enables us to increase the available ‘useful’ information obtained in a fixed scanning duration. Specifically, we successfully improve the theoretical precision of perfusion estimates by 4.6% compared to a scan design where the repetition times are randomly chosen (a popular choice in literature) thereby yielding a 35.2% improvement in the corresponding RMSE in our in-silico experiments. This improvement is also visually evident in our in-vivo studies on healthy human subjects.PHDElectrical and Computer EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169819/1/anishl_1.pd

Towards a nomadic utopianism: Gilles Deleuze and the good place that is no place

This thesis utilises the philosophy of Gilles Deleuze alongside theory from the field of 'utopian studies' in order to think through how the concepts of utopia and utopianism might be relevant in an age that seems to have given up on the future. It develops – and argues in favour of - a 'nomadic utopianism', which proceeds through non-hierarchical organisation, maximises what Deleuze calls 'difference-in-itself and creates new forms of living as it proceeds. From this, nomadic utopias are produced, meaning that the relationship between utopianism and utopia IS inverted, such that the former is ontologically prior to the latter. I show how such an approach maintains an etymological fidelity to the concept of utopia as 'the good place that is no place'. I also develop the concept of 'state utopianism', in which a utopian vision functions as a 'perfect', transcendent lack orienting political organisation to its realisation and reproduction. I argue that this is a dystopian politics, and consequently that the state utopia is a dystopia. Contrary to received wisdom - which sees today's 'capitalist realism' as anti-utopian – I argues that the contemporary world can be seen as a state utopia in which 'there is no alternative'. This makes utopia a central force in contemporary ideology. These two forms should not be seen simply as opposites, however, and this thesis also shows how nomadic utopias can ossify into state utopias through the emergence of tyrannies of habit. These theoretical concepts are then applied to works of utopian and dystopian literature (Yevgeny Zamyatin's We, Albert Meister's The so-called utopia of the centre beaubourg and Ursula K. Le Guin's The Dispossessed); and the practices of 'musicking' (with a focus on the symphony orchestra and collective improvisation) and education. It is hoped that this will offer a new way of theorising utopia and utopianism, as well as generating a productive political approach from the thought of Gilles Deleuze, and contributing to debates on the political function of musical and educational practice

Towards a nomadic utopianism: Gilles Deleuze and the good place that is no place

This thesis utilises the philosophy of Gilles Deleuze alongside theory from the field of 'utopian studies' in order to think through how the concepts of utopia and utopianism might be relevant in an age that seems to have given up on the future. It develops – and argues in favour of - a 'nomadic utopianism', which proceeds through non-hierarchical organisation, maximises what Deleuze calls 'difference-in-itself and creates new forms of living as it proceeds. From this, nomadic utopias are produced, meaning that the relationship between utopianism and utopia IS inverted, such that the former is ontologically prior to the latter. I show how such an approach maintains an etymological fidelity to the concept of utopia as 'the good place that is no place'. I also develop the concept of 'state utopianism', in which a utopian vision functions as a 'perfect', transcendent lack orienting political organisation to its realisation and reproduction. I argue that this is a dystopian politics, and consequently that the state utopia is a dystopia. Contrary to received wisdom - which sees today's 'capitalist realism' as anti-utopian – I argues that the contemporary world can be seen as a state utopia in which 'there is no alternative'. This makes utopia a central force in contemporary ideology. These two forms should not be seen simply as opposites, however, and this thesis also shows how nomadic utopias can ossify into state utopias through the emergence of tyrannies of habit. These theoretical concepts are then applied to works of utopian and dystopian literature (Yevgeny Zamyatin's We, Albert Meister's The so-called utopia of the centre beaubourg and Ursula K. Le Guin's The Dispossessed); and the practices of 'musicking' (with a focus on the symphony orchestra and collective improvisation) and education. It is hoped that this will offer a new way of theorising utopia and utopianism, as well as generating a productive political approach from the thought of Gilles Deleuze, and contributing to debates on the political function of musical and educational practice