In this research, a recent version of the Boreal Ecosystem Productivity Simulator (BEPS), called BEPS-TerrainLab, was adapted to northern peatlands and evaluated using observations made at the Mer Bleue bog located near Ottawa, Ontario, and the Sandhill fen located near Prince Albert, Saskatchewan. The code was extended and modified with a major focus on the adequate representation of northern peatlands' multi-layer canopy and the associated processes related to energy, water vapour and carbon dioxide fluxes through remotely-sensed leaf area index (LAI) maps. An important prerequisite for the successful mapping of LAI based on remote sensing imagery is the accurate measurement of LAI in the field with a standard technique such as the LAI-2000 plant canopy analyzer. As part of this research, a quick and reliable method to determine shrub LAI with the LAI-2000 instrument was developed. This method was used to collect a large number of LAI data at the Mer Bleue bog for the development of a new remote sensing-based methodology using multiple endmember spectral unmixing that allows for separate tree and shrub LAI mapping in ombrotrophic peatlands. A slight modification of this methodology allows for its application to minerotrophic peatlands and their surrounding landscapes. These LAI maps were used to explicitly represent the tree and shrub layers of the Mer Bleue bog and the tree and shrub/sedge layers of the Sandill fen within BEPS-TerrainLab. The adapted version of BEPS-TerrainLab was used to investigate the in fluence of mescoscale topography (Mer Bleue bog) and macro- and mesoscale topography (Sandhill fen) on wetness, evapotranspiration, and gross primary productivity during the snow-free period of 2004. This research suggests that future peatland ecosystem modelling efforts at regional and continental scales should include a peatland type-specific differentiation of macro- and mesoscale topographic effects on hydrology, to allow for a more realistic simulation of peatlands' soil water balance. This is an important prerequisite for the reduction of currently existing uncertainties in wetlands' contribution to North America's carbon dioxide and methane annual fluxes from an ecosystem modelling perspective.

In this research, a recent version of the Boreal Ecosystem Productivity Simulator (BEPS), called BEPS-TerrainLab, was adapted to northern peatlands and evaluated using observations made at the Mer Bleue bog located near Ottawa, Ontario, and the Sandhill fen located near Prince Albert, Saskatchewan. The code was extended and modified with a major focus on the adequate representation of northern peatlands' multi-layer canopy and the associated processes related to energy, water vapour and carbon dioxide fluxes through remotely-sensed leaf area index (LAI) maps. An important prerequisite for the successful mapping of LAI based on remote sensing imagery is the accurate measurement of LAI in the field with a standard technique such as the LAI-2000 plant canopy analyzer. As part of this research, a quick and reliable method to determine shrub LAI with the LAI-2000 instrument was developed. This method was used to collect a large number of LAI data at the Mer Bleue bog for the development of a new remote sensing-based methodology using multiple endmember spectral unmixing that allows for separate tree and shrub LAI mapping in ombrotrophic peatlands. A slight modification of this methodology allows for its application to minerotrophic peatlands and their surrounding landscapes. These LAI maps were used to explicitly represent the tree and shrub layers of the Mer Bleue bog and the tree and shrub/sedge layers of the Sandill fen within BEPS-TerrainLab. The adapted version of BEPS-TerrainLab was used to investigate the in fluence of mescoscale topography (Mer Bleue bog) and macro- and mesoscale topography (Sandhill fen) on wetness, evapotranspiration, and gross primary productivity during the snow-free period of 2004. This research suggests that future peatland ecosystem modelling efforts at regional and continental scales should include a peatland type-specific differentiation of macro- and mesoscale topographic effects on hydrology, to allow for a more realistic simulation of peatlands' soil water balance. This is an important prerequisite for the reduction of currently existing uncertainties in wetlands' contribution to North America's carbon dioxide and methane annual fluxes from an ecosystem modelling perspective.

This paper investigates the viability of two different mappings of two parameters of the digital musical instrument Force Ghost. The instrument produces sound by having an  ambience (a recording of rain or of waves on the beach) filtered by bandpass filters  whose center-frequencies are controlled by a midi-keyboard. Five bandpass filters are assigned to each note, corresponding to the fundamental frequency its and its multiples (2f,3f,4f,5f). The mapped parameters are the Q-factor of the bandpass filters and the timbre, defined as the relative level between the even and odd multiples harmonics. These two parameters are mapped to the modulation wheel and the pitch bend wheel. The mappings of the parameters are investigated with the help of musical tasks completed by musicians rounded up with semi-structured interviews. The interviews revealed that the modulation wheel was to be prefered due to the lack of a spring mechanism (which is an attribute of the pitch bend wheel), forcing the wheel back to its default position (in the middle) when released. The results from the musical tasks suggested an indication that none of the sensors have better controllability than the other, regardless of parameter it controls. In conclusion, a sensor that gravitates towards a resting state does not seem to be suitable to control a parameter (scaling) that lacks a “resting value” (as perceived by musicians). / Denna artikel utreder två mappningar av två parametrar hos det digitala musikaliska instrumentet Force Ghost. Instrumentet ljuder genom att en ljudkälla filtreras av bandpassfilter. Ljudkällan i detta fall är ljudet av regnfall i en skog. Varje tangent på ett keyboard är kopplat till minst ett bandpassfilter, vars MIDI-not kopplat till motsvarande frekvens. Denna frekvens är bandpassfiltrets centerfrekvens. När en tangent nedtrycks genereras bandpassfiltret, vilket skapar en ton ur ljudkällan. De två parametrarna i fokus är kopplade till bandpassfiltrerna. De är Q-värdet (kopplat till bandpassfiltrernas bandbredd) och klangfärgen (kopplat till övertonerna; vilka de är och deras amplitudrelation för varje not). Dessa två parametrar är mappade till modulations-hjulet och pitchbend-hjulet. Mappningen av dessa parametrar är undersökt genom musikuppgifter och självständig utforskning genomförda av musiker. Detta spelades in och sedan utfördes en semistrukturerad intervju med musikerna. Intervjuerna visade att modulations-hjulet föredrogs på grund av avsaknaden av fjädermekanismen som finns hos pitchbend-hjulet. Denna mekanism tvingar pitchbend-hjulet tillbaka till sin utgångsposition (i mitten) när den släpps. Resultaten från musikuppgifterna indikerar att ingen av sensorerna har bättre kontrollbarhet än den andre, oavsett vilket parameter den kontrollerar. Sammanfattningsvis, en sensor som graviterar mot ett viloläge verkar inte vara lämplig för att kontrollera en parameter (-skalning) som saknar ett “vilovärde” (så som uppfattat av musiker).

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The clinical utility of multi-dimensional MRI applications like multi-parameter mapping and 3D dynamic lung imaging is limited by long acquisition times. Quantification of multiple tissue MRI parameters has been shown to be useful for early detection and diagnosis of various neurological diseases and psychiatric disorders. They also provide useful information about disease progression and treatment efficacy. Dynamic lung imaging enables the diagnosis of abnormalities in respiratory mechanics in dyspnea and regional lung function in pulmonary diseases like chronic obstructive pulmonary disease (COPD), asthma etc. However, the need for acquisition of multiple contrast weighted images as in case of multi-parameter mapping or multiple time points as in case of pulmonary imaging, makes it less applicable in the clinical setting as it increases the scan time considerably. In order to achieve reasonable scan times, there is often tradeoffs between SNR and resolution. Since, most MRI images are sparse in known transform domain; they can be recovered from fewer samples. Several compressed sensing schemes have been proposed which exploit the sparsity of the signal in pre-determined transform domains (eg. Fourier transform) or exploit the low rank characteristic of the data. However, these methods perform sub-optimally in the presence of inter-frame motion since the pre-determined dictionary does not account for the motion and the rank of the data is considerably higher. These methods rely on two step approach where they first estimate the dictionary from the low resolution data and using these basis functions they estimate the coefficients by fitting the measured data to the signal model. The main focus of the thesis is accelerating the multi-parameter mapping and 3D dynamic lung imaging applications to achieve desired volume coverage and spatio-temporal resolution. We propose a novel dictionary learning framework called the Blind compressed sensing (BCS) scheme to recover the underlying data from undersampled measurements, in which the underlying signal is represented as a sparse linear combination of basic functions from a learned dictionary. We also provide an efficient implementation using variable splitting technique to reduce the computational complexity by up to 15 fold. In both multi- parameter mapping and 3D dynamic lung imaging, the comparisons of BCS scheme with other schemes indicates superior performance as it provides a richer presentation of the data. The reconstructions from BCS scheme result in high accuracy parameter maps for parameter imaging and diagnostically relevant image series to characterize respiratory mechanics in pulmonary imaging.

Recovering a linear combination of exponential signals characterized by parameters is highly significant in many MR imaging applications such as parameter mapping and spectroscopy. The parameters carry useful clinical information and can act as biomarkers for various cardiovascular and neurological disorders. However, their accurate estimation requires a large number of high spatial resolution images, resulting in long scan time. One of the ways to reduce scan time is by acquiring undersampled measurements. The recovery of images is usually posed as an optimization problem, which is regularized by functions enforcing sparsity, smoothness or low rank structure. Recently structured matrix priors have gained prominence in many MRI applications because of their superior performance over the aforementioned conventional priors. However, none of them are designed to exploit the smooth exponential structure of the 3D dataset. In this thesis, we exploit the exponential structure of the signal at every pixel location and the spatial smoothness of the parameters to derive a 3D annihilation relation in the Fourier domain. This relation translates into a product of a Hankel/Toeplitz structured matrix, formed from the k-t samples, and a vector of filter coefficients. We show that this matrix has a low rank structure, which is exploited to recover the images from undersampled measurements. We demonstrate the proposed method on the problem of MR parameter mapping. We compare the algorithm with the state-of-the-art methods and observe that the proposed reconstructions and parameter maps have fewer artifacts and errors. We extend the structured low rank framework to correct field inhomogeneity artifacts in MR images. We introduce novel approaches for field map compensation for data acquired using Cartesian and non-Cartesian trajectories. We adopt the time segmentation approach and reformulate the artifact correction problem into a recovery of time series of images from undersampled measurements. Upon recovery, the first image of the series will correspond to the distortion-free image. With the above re-formulation, we can assume that the signal at every pixel follows an exponential signal characterized by field map and the damping constant R2*. We exploit the smooth exponential structure of the 3D dataset to derive a low rank structured matrix prior, similar to the parameter mapping case. We demonstrate the algorithm on spherical MR phantom and human data and show that the artifacts are greatly reduced compared to the uncorrected images. Finally, we develop a structured matrix recovery framework to accelerate cardiac breath-held MRI. We model the cardiac image data as a 3D piecewise constant function. We assume that the zeros of a 3D trigonometric polynomial coincides with the edges of the image data, resulting in a Fourier domain annihilation relation. This relation can be compactly expressed in terms of a structured low rank matrix. We exploit this low rank property to recover the cardiac images from undersampled measurements. We demonstrate the superiority of the proposed technique over conventional sparsity and smoothness based methods. Though the model assumed here is not exponential, yet the proposed algorithm is closely related to that developed for parameter mapping. The direct implementation of the algorithms has a high memory demand and computational complexity due to the formation and storage of a large multi-fold Toeplitz matrix. Till date, the practical utility of such algorithms on high dimensional datasets has been limited due to the aforementioned reasons. We address these issues by introducing novel Fourier domain approximations which result in a fast and memory efficient algorithm for the above-mentioned applications. Such approximations allow us to work with large datasets efficiently and eliminate the need to store the Toeplitz matrix. We note that the algorithm developed for exponential recovery is general enough to be applied to other applications beyond MRI.

Background: Fetal alcohol spectrum disorders (FASD), which are caused by prenatal alcohol exposure (PAE), affects people around the world. Certain communities in South Africa have among the highest reported incidences of fetal alcohol syndrome (FAS) in the world. Although PAE-related brain alterations have been widely documented, the mechanisms whereby alcohol affects the brain are not clearly understood. MRI relaxation parameters T1, T2, T2* and proton density (PD), are basic tissue properties that reflect the underlying biology. The present study aims to advance our understanding of how PAE alters the microstructural properties of tissue by examining PAE-related changes in these tissue parameters in adolescents with FASD. Methods: The final sample used in this study consisted of 53 children from a previously studied longitudinal cohort (Jacobson et al., 2008) and 12 additionally recruited subjects. Of the 65 participants, 18 were diagnosed with FAS or partial FAS (PFAS) and made up the FAS/PFAS group, 18 were diagnosed as heavily exposed non-syndromal (HE) and 29 were age matched controls. Subjects were scanned at the Cape Universities Body Imaging Centre (CUBIC) located at Groote Schuur Hospital on a 3T Siemens Skyra MRI. Structural images were obtained using the MEMPRAGE sequence. From these images T1, T2, T2* and PD parameter maps were constructed and segmented into 43 regions of interest (ROI) using Freesurfer, FSL and AFNI. Linear regression analyses were used to analyse group differences as well as correlations between parameter values and the amount of alcohol the mother consumed during pregnancy. Results: Significant T1 differences were found in the caudate, cerebellar cortex, hippocampus, accumbens, putamen, choroid plexus, ventral diencephalon (DC), right vessel and ventricles. Significant T2 differences were found in the caudate, brain stem, corpus callosum (CC), amygdala, cerebral cortex, choroid plexus, vessels and ventricles. Significant T2* differences were found in the cerebellar cortex, optic chiasm and ventricles. Significant PD differences were found in the hippocampus and left lateral ventricle. The exploratory nature of this study resulted in none of the results surviving FDR correction for multiple comparisons. Conclusions: Overall, our findings point to regional PAE-related increases in water content and cellular and molecular changes in underlying tissue of the anatomical structure. Exceptions were the right cerebral cortex, brain stem, hippocampus, amygdala and ventral diencephalon where our findings point to less free water and increased cell density, and cerebellar cortex where simultaneous reductions in T1 and T2* suggest the possibility of increased iron content. In highly myelinated white matter structures, such as the CC and optic chiasm, our results point to PAErelated demyelination, and possibly increased iron. These findings extend previous knowledge of effects of PAE and demonstrate that tissues are affected at a microstructural level.

The affect on leaf area index (LAI) and net ecosystem production (NEP) of the mountain pine beetle (Dendroctonus ponderosae) (MPB) outbreak in British Columbia affecting lodgepole pine (Pinus contorta var. latifolia) forests was examined from 1999 to 2008. The process-based carbon (C) cycle model – Boreal Ecosystem Productivity Simulator (BEPS) with remotely sensed LAI inputs was used to produce annual NEP maps, which were validated using field measurements. The annual NEP ranged from 2.43 to -8.03 MtC between 1999 and 2008, with sink to source conversion in 2000. The inter-annual variability for both LAI and NEP displayed initial decreases followed by a steadily increasing trend from 2006 to 2008 with NEP returning to near C neutrality in 2008 (-1.84 MtC). The resistance of LAI and NEP to MPB attack was attributed to ecosystem resilience in the form of secondary overstory growth and increased production of non-attacked host trees.

The affect on leaf area index (LAI) and net ecosystem production (NEP) of the mountain pine beetle (Dendroctonus ponderosae) (MPB) outbreak in British Columbia affecting lodgepole pine (Pinus contorta var. latifolia) forests was examined from 1999 to 2008. The process-based carbon (C) cycle model – Boreal Ecosystem Productivity Simulator (BEPS) with remotely sensed LAI inputs was used to produce annual NEP maps, which were validated using field measurements. The annual NEP ranged from 2.43 to -8.03 MtC between 1999 and 2008, with sink to source conversion in 2000. The inter-annual variability for both LAI and NEP displayed initial decreases followed by a steadily increasing trend from 2006 to 2008 with NEP returning to near C neutrality in 2008 (-1.84 MtC). The resistance of LAI and NEP to MPB attack was attributed to ecosystem resilience in the form of secondary overstory growth and increased production of non-attacked host trees.