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The Kombi Trail
Cambridge, 1961. A group of students set off on the trip of a lifetime. Against the backdrop of the Cold War they travel through the Soviet Union to the Middle East, South Asia and on to Africa. Their mode of transport? The iconic VW Kombi. This book tells the story of that trip, not just the people they met and the places they saw, but the many experiences - sometimes nerve-wracking, sometimes bizarre - that they encountered along the way. It provides a fascinating insight into a world on the brink of change - seen through the eyes of nine young men fresh from university. The two VW Kombis doggedly traversed treacherous mountain passes, near-impossible roads, jungle tracks and river crossings on their journey through Anatolia, the Middle East, Asia and Africa. This book is an affectionate and highly entertaining re-creation of the relationship between the nine young travellers and their companions, the two VW Kombis which functioned as transport, shelter, canteen and home. It is also a tribute to the determined and rugged determination of the VW Kombi whose descendants still tackle the highways and the more daunting roads of the world.
eBook
An Effective Diffeomorphic Model and Its Fast Multigrid Algorithm for Registration of Lung CT Images
Image registration is the process of aligning sets of similar, but different, intensity image functions to track changes between the images. In medical image problems involving lung images, variational registration models are a very powerful tool which can aid in effective treatment of various lung conditions and diseases. However, a common drawback of many variational models, such as the diffusion model and even optic flow models,
is the lack of control of folding in the deformations leading to physically inaccurate transformations. For this reason, such models are generally not suitable for real life lung imaging problems where folding cannot occur.
There are two approaches offering reliable solutions (though not necessarily accurate).
The first approach is a parametric model such as the affine registration model, still widely used in many applications, but is unable to track local changes or yield accurate results.
The second approach is to impose an extra constraint on the transformation of registration
at the cost of increased non-linearity.
An alternative to the second approach, achieving diffeomorphic transforms without adding any constraints, is an inverse consistent model such as by Christensen and Johnson (2001) from computing explicitly both the forward and inverse transforms. However, one must deal with the strong non-linearity in the formulation.
In this paper we first propose a simplified inverse consistent model to avoid the inclusion of strong non-linearities and then a fast non-linear multigrid (NMG) technique to overcome the extra computational work required by the inverse consistent model. Experiments, performed on real medical CT images, show that our proposed inverse consistent model is robust to both parameter choice and non-folding in the transformations when compared with diffusion type models.
Journal Article
Sums of Positive Integral Powers
Ryang and Thompson present one approach to investigating the sums of positive integral powers using methods accessible to high school and college teachers and their students. In conclusion, a rich literature is associated with sums of integer powers, with many different approaches to computing formulas for Σk. Interesting historical connections exist as well, quite a number of which are surveyed by Beery (2009). Of particular note is the work of Jacob Bernoulli (1654-1705) and the development of Bernoulli numbers. The handshake and cannonball problems that most middle school and high school students know well can lead in a natural way to many interesting extensions. Teachers as well as advanced high school students and college students enjoy the opportunity to investigate these extensions, and the methods presented here provide one avenue for doing so.
Journal Article
Poemhood, our black revival : history, folklore & the Black experience: a young adult poetry anthology
Featuring contributions from an award-winning, bestselling group of Black voices, past and present, this powerful poetry anthology elicits vital conversations about race, belonging, history and faith to highlight Black joy and pain.
Book
Motion Correction of Lung CT Images with an Application to Oncology
The aim of image registration is to align sets of similar images which have been captured at different time points, from different perspectives or obtained using different imaging modalities (e.g. CT, MRI, X-ray). In oncology, image registration is a very powerful tool which can be used in an array of different applications such as anatomic image segmentation, 4D dose accumulation maps and lung ventilation maps. In order to align a given set of images, we first assign one image in the set to be the 'fixed' reference image to which we align the remaining 'moving' template images. We are then tasked with finding suitable transformations which deform the template images to match the reference image. In this thesis, we model the image registration problem mathematically through the minimisation of an energy functional. We begin by proposing an improved non-linear multigrid method, based upon the method proposed by Chumchob and Chen in 33, via a more accurate analysis of the scheme and new solver to improve convergence, accuracy and CPU time. Next we extend our improved Chumchob-Chen model to incorporate an additional constraint to prevent folding in the transformation, thus leading to physically accurate diffeomorphic registrations. After this we further extend our proposed constrained model to improve robustness with regard to accuracy in cases of severe folding, in addition to parameter choice. We then demonstrate these improvements using a combination of real lung CT images and a synthetic hand X-ray image set. Next we consider a different approach to addressing the problem of folding in the transformation, by formulating an inverse consistent image registration model based upon the model first proposed by Christensen and Johnson in 28. Our proposed idea is to linearise the inverse consistency constraint in the Christensen-Johnson model, which is extremely expensive to compute with regard to computational cost due to its non-linear nature, in addition to implementing a fast non-linear multigrid scheme to further help reduce the computational cost of the model. We then perform some numerical tests on a mix of real CT images and a synthetic example, to highlight the advantages of our proposed inverse consistent model. Finally, we present three 3D image registration models based upon the models discussed throughout this thesis, in addition to 3D extensions of the associated non-linear multi grid schemes. We then show some preliminary results, using eight examples taken from the Hugo image database 80 along with clinically drawn contours for nine different objects within the CT images, comparing our proposed models with a state of the art commercial software used in hospitals.
Dissertation
Relating Unidimensional IRT Parameters to a Multidimensional Response Space: A Review of Two Alternative Projection IRT Models for Scoring Subscales
A practical concern for many existing tests is that subscore test lengths are too short to provide reliable and meaningful measurement. A possible method of improving the subscale reliability and validity would be to make use of collateral information provided by items from other subscales of the same test. To this end, the purpose of this article is to compare two different formulations of an alternative Item Response Theory (IRT) model developed to parameterize unidimensional projections of multidimensional test items: Analytical and Empirical formulations. Two real data applications are provided to illustrate how the projection IRT model can be used in practice, as well as to further examine how ability estimates from the projection IRT model compare to external examinee measures. The results suggest that collateral information extracted by a projection IRT model can be used to improve reliability and validity of subscale scores, which in turn can be used to provide diagnostic information about strength and weaknesses of examinees helping stakeholders to link instruction or curriculum to assessment results.
Journal Article