Dr Michael Braun

Hutton, B.F., Braun, M. & Slomka, P. 2006, 'Image registration techniques in nuclear medicine imaging' in Zaidi H (ed), Quantitative Analysis in Nuclear Medicine Imaging, Springer, New York, USA, pp. 272-307.
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Neclear medicine has a long tradition of incorporating quantitative analysis in its diagnostic procedures. Until recently, the analysis was based on radionuclide images as the sole input although the importance of the complementary information available from other modalities or from earlier scans has long been recognised. Indeed, qualitative correlation between images, based on anatomical expertise, has always been part of the repertoire of nuclear medicine clinician. However, spatial distortiom netween images, caused largely by differences in posture and acquisition technique, prevented the extension of these techniques to quantitative analysis. Recent advances in image registration software and hardware have made it increasingly possible to utilise that complementary image information in a clinical setting.

Yunusa, I.A., Braun, M. & R, L. 2009, 'Amendment of soil with coal fly ash modified burrowing habits of two earthworm species', Applied Soil Ecology, vol. 42, no. 1, pp. 63-68.
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A good understanding of how soil biota responds to amendment of agricultural soils with coal fly ash is imperative to developing protocols for routine use of this industrial by-product for soilmanagement. We used X-ray computed tomography (CT) images to determined key structural characteristics of burrows created by earthworms of native megascolecid and exotic Aporrectodea trapezoides in intact soil cores (150 mm ID by 0.3 m deep) that were treated with coal fly ash at 0, 5 or 25 Mg ha 1 mixed into the top 50 mm of the cores. The cores were inoculated at a rate equivalent to 850 worms m 2 and after 6 weeks we found that fly ash reduced the total volume of the burrow system (Vs) by up to 39% for the native species and 29% for the exotic species due mostly to fewer and smaller burrows; these reductions averaged 33% with addition of ash at 5 Mg ha 1 and 39% at 25 Mg ha 1. While the native earthworms responded to treatment by burrowing deeper into the soil core and away from the ash-tainted surface soil, the exotic species reduced the depth of burrowing and remained close to the surface. Fly ash addition did not have significant effect on tortuosity (t) of the burrows for either earthworm species. A. trapezoides created predominantly vertical burrows, while the native megascolecid worms produced more horizontally oriented burrows in addition to vertical ones. These modifications of earthworm behavior by fly ash addition to soil, along with previous experience with plant growth, suggest that an ash application rate of 5 Mg ha 1is close to optimum for routine agronomic applications. Structural analysis of the burrows as presented in this paper provide more useful information on the response of earthworm behaviour to fly ash that may not be apparent from an assessment of population and growth of these important soil biota.

Hutton, B.F., Olsson, A., Erlandsson, K. & Braun, M. 2006, 'Reducing the influence of spatial resolution to improve quantitative accuracy in emission tomography: a comparison of potential strategies', Nuclear Instrumentation & Methods in Physics Research Section A, vol. 569, no. 2, pp. 462-466.
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The goal of this paper is to compare strategies for reducing partial volume effects by either minimising the cause (i.e. improving resolution) or correcting the effect. Correction for resolution loss can be achieved either by modelling the resolution for ise in iterative reconstruction or by imposing contraints based on knowledge of the underlying anatomy. Approaches to partial volume correctiuon largely rely on knoweldge of the underlying anatomy, based on well-registered high-resolution anatomical imaging modalities (CT ot MRI). Corrections can be applied bu considering the signal loss that results by smoothing the high-resolution modality to the same resolution as obntained in emission tomography. A physical phantom representing the central brain structures was used to evaluate the quantitative accuracy of the various strategies for either improving resolution or correcting for partial volume effects. Inclusion of resolution in the reconstruction model imporved the measured contrast for the central brain structures but still underestimated the true object contrast (~0.70). Use of information on the boundaries of the structures in conjunction with a smoothing prior using maximum entropy reconstruction achieved some degree of contrast enhancement and improved the noise properties of the resulting images. Partial volume correction based on segmentation of registered anatomical images and knowledge of the reconstructred resolution permitted more accurate quantificationm of the target to background ration for individual brain structures.

Hutton, B.F. & Braun, M. 2003, 'Software for image fusion: algorithms, accuracy, efficacy', Seminars in Nuclear Medicine, vol. 33, no. 3, pp. 180-192.
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Zhang, Z. & Braun, M. 2003, 'Smoothness-based forces for deformable models: a long-range force and a corner fitting force', Computers In Biology And Medicine, vol. 33, no. 1, pp. 91-112.
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Hutton, B.F., Braun, M., Thurfjell, L. & Lau, D.Y. 2002, 'Image registration: an essential tool for nuclear medicine', European Journal of Nuclear Medicine, vol. 29, no. 4, pp. 559-577.
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Lau, Y.H., Braun, M., Hutton, B.F. 2001, 'Non-Rigid Image Registation Using a Median-Filetered Coarse-to-Fine Displacement Field and a Symmetric Correlation Ratio', Physics in Medicine & Biology, vol. 46, no. 2, pp. 1297-1319.
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Conventional approaches to image registration are generally limited to image-wide rigid transformations. However, the body and its internal organs are non-rigid structures that change shape due to changes in the body's posture during image acquisition, and due to normal, pathological and treatment-related variations. Inter-subject matching also constitutes a non-rigid registration problem. In this paper, we present a fully automated non-rigid image registration method that maximizes a local voxel-based similarity metric. Overlapping image blocks are defined on a 3D grid. The transformation vector field representing image deformation is found by translating each block so as to maximize the local similarity measure. The resulting sparsely sampled vector field is median filtered and interpolated by a Gaussian function to ensure a locally smooth transformation. A hierarchical strategy is adopted to progressively establish local registration associated with image structures at diminishing scale. Simulation studies were carried out to evaluate the proposed algorithm and to determine the robustness of various voxel-based cost functions. Mutual information, normalized mutual information, correlation ratio (CR) and a new symmetric version of CR were evaluated and compared. A T1-weighted magnetic resonance (MR) image was used to test intra-modality registration. Proton density and T2-weighted MR images of the same subject were used to evaluate inter-modality registration. The proposed algorithm was tested on the 2D MR images distorted by known deformations and 3D images simulating inter-subject distortions. We studied the robustness of cost functions with respect to image sampling. Results indicate that the symmetric CR gives comparable registration to mutual information in intra- and inter-modality tasks at full sampling and is superior to mutual information in registering sparsely sampled images.