Diffeomorphic Demons using Normalised Mutual Information, Evaluation on Multi-Modal Brain MR Images

The demons algorithm is a fast non-parametric non-rigid registration method. In recent years great efforts have been made to improve the approach; the state of the art version yields symmetric inverse-consistent large-deformation diffeomorphisms. However, only limited work has explored inter-modal similarity metrics, with no practical evaluation on multi-modality data. We present a diffeomorphic demons implementation using the analytical gradient of Normalised Mutual Information (NMI) in a conjugate gradient optimiser. We report the first qualitative and quantitative assessment of the demons for inter-modal registration. Experiments to spatially normalise real MR images, and to recover simulated deformation fields, demonstrate (i) similar accuracy from NMI-demons and classical demons when the latter may be used, and (ii) similar accuracy for NMI-demons on T1w-T1w and T1w-T2w registration, demonstrating its potential in multi-modal scenarios

Diffeomorphic demons using normalized mutual information, evaluation on multimodal brain MR images

The demons algorithm is a fast non-parametric non-rigid registration method. In recent years great efforts have been made to improve the approach; the state of the art version yields symmetric inverse-consistent largedeformation diffeomorphisms. However, only limited work has explored inter-modal similarity metrics, with no practical evaluation on multi-modality data. We present a diffeomorphic demons implementation using the analytical gradient of Normalised Mutual Information (NMI) in a conjugate gradient optimiser. We report the first qualitative and quantitative assessment of the demons for inter-modal registration. Experiments to spatially normalise real MR images, and to recover simulated deformation fields, demonstrate (i) similar accuracy from NMI-demons and classical demons when the latter may be used, and (ii) similar accuracy for NMI-demons on T1w-T1w and T1w-T2w registration, demonstrating its potential in multi-modal scenarios

Multicanonical Cluster Algorithm and the 2-D 7-State Potts Model

I present a hybrid-like two-step algorithm, which combines a microcanonical update of a spin system using demons, with a multicanonical demon refresh. The algorithm is free from the supercritical slowing down that burdens the canonical methods: the exponential increase of the tunnelling time between the metastable states in the first-order phase transitions, when the volume of the system is increased. The demons act as a buffer between the multicanonical heat bath and the spin system, allowing the spin system to be updated with any microcanonical demon procedure, including cluster methods. The cluster algorithm is demonstrated with the 2-dimensional 7-state Potts model, using volumes up to $128^2$. The tunnelling time is found to increase as $L^{1.82}$, where $L$ is the linear dimension of the system.Comment: 14 pages, 8 ps-figures, the flashy one missing to save space+troubles, sorry, the whole thing available from the author. Preprint CERN-TH.6654/9

Stavrogin: The Anti-Christ of Demons

Fyodor Dostoevsky’s novel Demons is much more than the story of a political murder; it describes the clash of ideas in 1860s Russia as Russia battles between retaining its past national identity, rooted loosely in Eastern Orthodoxy, and Western ideas, rooted in atheism. It is a clash of politics, but even more it is a clash of religion. However, the opposing sides in the battle of religion appear far from balanced, for even Shatov, who supports Russian Orthodoxy, does not truly believe in God. Atheism seems to win out as all characters reject real, vital faith in God in some form, and havoc ensues. At the center of it all lies the enigmatic, fascinating, horrifying character Stavrogin. Though Stavrogin often lies in the background, rarely doing anything and often fading out altogether, his subtle yet powerful influence over the other characters drives the plot of the novel. Through it all, Demons sets Stavrogin up as an anti-Christ figure, hammering the dreadful consequences of replacing God with man

Multipartite information flow for multiple Maxwell demons

The second law of thermodynamics dictates the fundamental limits to the amount of energy and information that can be exchanged between physical systems. In this work, we extend a thermodynamic formalism describing this flow of energy and information developed for a pair of bipartite systems to many multipartite systems. We identify a natural thermodynamic quantity that describes the information exchanged among these systems. We then introduce and discuss a refined version. Our results are illustrated with a model of two, competing Maxwell demons.Comment: 13 pages, 3 figure