Diffusional kurtosis imaging using a fast heuristic constrained linear least squares algorithm: a plugin for OsiriX

Diffusion Kurtosis Imaging (DKI) is a fairly new magnetic resonance imag-ing (MRI) technique that tackles the non-gaussian motion of water in biological tissues by taking into account the restrictions imposed by tissue microstructure, which are not considered in Diffusion Tensor Imaging (DTI), where the water diffusion is considered purely gaussian. As a result DKI provides more accurate information on biological structures and is able to detect important abnormalities which are not visible in standard DTI analysis. This work regards the development of a tool for DKI computation to be implemented as an OsiriX plugin. Thus, as OsiriX runs under Mac OS X, the pro-gram is written in Objective-C and also makes use of Apple’s Cocoa framework. The whole program is developed in the Xcode integrated development environ-ment (IDE). The plugin implements a fast heuristic constrained linear least squares al-gorithm (CLLS-H) for estimating the diffusion and kurtosis tensors, and offers the user the possibility to choose which maps are to be generated for not only standard DTI quantities such as Mean Diffusion (MD), Radial Diffusion (RD), Axial Diffusion (AD) and Fractional Anisotropy (FA), but also DKI metrics, Mean Kurtosis (MK), Radial Kurtosis (RK) and Axial Kurtosis (AK).The plugin was subjected to both a qualitative and a semi-quantitative analysis which yielded convincing results. A more accurate validation pro-cess is still being developed, after which, and with some few minor adjust-ments the plugin shall become a valid option for DKI computation

Comments on ‘‘Modeling fractional stochastic systems as non-random fractional dynamics driven Brownian motions

Applied Mathematical Modelling, Vol.33

A coherent approach to non-integer order derivatives

Signal Processing, vol. 86, nº 10

Digital-domain self-calibration technique for video-rate pipeline A/D converters using Gaussian white noise

Electronics Letters Vol.38, nº 19

Low-voltage low-power CMOS analogue circuits for Gaussian and uniform noise generation

IEEE International Symposium on Circuits and Systems, MAY 25-28, 2003, Bangkok, Thailand. (ISI Web of Science)

Multi-bit sigma-delta modulators with enhanced dynamic-range using non-linear DAC for hearing aids

15th IEEE International Conference on Electronics, Circuits and Systems, Malta

Non-volatile analysis in fruits by laser resonant ionization spectrometry: application to resveratrol (3,5,4 -trihydroxystilbene) in grapes

Applied Physics B Lasers and Optics, vol.71

Efficient digital self-calibration of video-rate pipeline ADCs using white gaussian noise

Proceedings of IEEE, ISCAS 2003, Vol.I, pp. 877-880

FROM NON-PLACE TO PLACE: A STUDY OF EUROPEAN PUBLIC SPACE AS A SPACE OF IDENTITY

Master Erasmus Mundus Crossways in European Humanities

Archaeological roman glasses: comparative characterisation by non-destructive analytical techniques

Dissertation presented in fulfilment of the requirements for the Master’s degree in Conservation and Restoration

Negative non-ground queries in well founded semantics

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Computational Logic

AVTEM NON SVNT RERVM NATVRA. Figurações heteromórficas em mosaicos hispano-romanos

Tese apresentada para cumprimento dos requisitos necessários à obtenção do grau de Doutor em História da Arte da Antiguidade

Non-linear time series models

The last three decades have seen quite dramatic changes the way we modeled time dependent data. Linear processes have been in the center stage in modeling time series. As far as the second order properties are concerned, the theory and the methodology are very adequate.However, there are more and more evidences that linear models are not sufficiently flexible and rich enough for modeling purposes and that failure to account for non-linearities can be very misleading and have undesired consequences.

A score test for non-nested hypotheses with applications to discrete data models

This paper suggests that a convenient score test against non-nested alternatives can be constructed from the linear combination of the likelihood functions of the competing models. It is shown that this procedure is essentially a test for the correct specification of the conditional distribution of the variable of interest.

Contribuição ao estudo da mistura néon-azoto a baixas temperaturas

Dissertação para obtenção do Grau de Mestre em Engenharia Física