Directionality of Cavities and Porosity Formation in Powder-Bed Laser Additive Manufacturing of Metal Components Investigated Using X-Ray Tomography

Published ArticleEnsuring additive manufactured metal components are free of major defects is crucial to the application of this new technology in medical and aerospace industries. One source of defects in such parts is lack of fusion in individual locations or specific layers. Such lack of melting or fusion could be the result of a nonflat powder bed due to an imperfect recoating blade or loose support structures causing recoating problems. Another possible source is laser power fluctuations or beam size fluctuations, or even ambient humidity or temperature changes, among others. The aims of this article are to investigate lack of fusion with planned induced defects (cavities) with different three-dimensional (3D) geometries and analyze these using nondestructive 3D X-ray tomography. It is found that some fusion occurs in induced defect layers and lines perpendicular to the build direction (XY) up to 180 lm in height. This means fusion occurs through fused layers above cavities, minimizing defect formation in the plane of the build platform. In contrast, in the case of vertical cavities (cavity walls) parallel to the build direction, much larger defects are observed compared to the above case. This result may point to the build direction (vertical) being more favorable for porosity formation under nonideal conditions (i.e., a preferred directionality). An example of unexpected porosity trail formation in the build direction is also reported from such nonideal conditions for a real part in contrast to a designed cavity

Indirect Detection of Axonal Architecture With Q-Space Imaging

Evaluating axon morphology would provide insights into connectivity, maturation, and disease pathology. Conventional diffusion MRI can provide metrics that are related to axon morphology, but cannot measure specific parameters such as mean axon diameter (MAD) and intracellular fraction (ICF). Q-space imaging (QSI) is an advanced diffusion MRI technique that may be able to provide more information on axon morphology. However, QSI has several limitations that affect its implementation and accuracy. The main objective of this dissertation was to address these limitations and to evaluate the potential of QSI to accurately assess axon morphology. First, a custom-built high-amplitude gradient coil was used to address the limitations in the maximum gradient amplitude available with commercial systems. Second, to understand the relationship between axon morphology and QSI, simulations were used to investigate the effects of the presence of both extracellular and intracellular signals (ECS and ICS) as well as variation in cell size and shape. Third, three QSI-based methods were designed provide specific measures of axon morphology which have not been reported before. The maximum amplitude of the custom gradient coil was 50 T/m that, for the first time, allowed for sub-micron displacement resolution while fulfilling the short gradient approximation. This enabled near-ideal QSI experiments to be performed. QSI experiments on excised mouse spinal cords showed good correlation with histology, but overestimated MAD. Simulations showed that axon morphology was the dominant effect on QSI and suggested that the presence of ECS and ICS signals may complicate interpretation. Three methods were designed to account for signal in ECS and ICS: two relied on a two-compartment model of the displacement probability density function and the echo attenuation at low q-values, and a third varied the gradient duration to differentiate diffusion in ECS from ICS. All three methods provided estimates of MAD and ICF that showed better agreement with histology than QSI. The methods were also evaluated implementation on a clinical scanner. This dissertation demonstrated the sensitivity of QSI to axon morphology and showed the feasibility of three methods to accurately estimate MAD and ICF. Further investigation is warranted to study future applications

Integration of anatomical and hemodynamical information in magnetic resonance angiography

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A robust coregistration method for in vivo studies using a first generation simultaneous PET/MR scanner

Purpose: Hybrid positron emission tomography (PET)/magnetic resonance (MR) imaging systems have recently been built that allow functional and anatomical information obtained from PET and MR to be acquired simultaneously. The authors have developed a robust coregistration scheme for a first generation small animal PET/MR imaging system and illustrated the potential of this system to study intratumoral heterogeneity in a mouse model. Methods: An alignment strategy to fuse simultaneously acquired PET and MR data, using the MR imaging gradient coordinate system as the reference basis, was developed. The fidelity of the alignment was evaluated over multiple study sessions. In order to explore its robustness in vivo, the alignment strategy was applied to explore the heterogeneity of glucose metabolism in a xenograft tumor model, using ^(18)F-FDG-PET to guide the acquisition of localized ^1H MR spectra within a single imaging session. Results: The alignment method consistently fused the PET/MR data sets with subvoxel accuracy (registration error mean=0.55 voxels, <0.28 mm); this was independent of location within the field of view. When the system was used to study intratumoral heterogeneity within xenograft tumors, a correlation of high ^(18)F-FDG-PET signal with high choline/creatine ratio was observed. Conclusions: The authors present an implementation of an efficient and robust coregistration scheme for multimodal noninvasive imaging using PET and MR. This setup allows time-sensitive, multimodal studies of physiology to be conducted in an efficient manner

Automated Three-Dimensional Detection and Shape Classification of Dendritic Spines from Fluorescence Microscopy Images

A fundamental challenge in understanding how dendritic spine morphology controls learning and memory has been quantifying three-dimensional (3D) spine shapes with sufficient precision to distinguish morphologic types, and sufficient throughput for robust statistical analysis. The necessity to analyze large volumetric data sets accurately, efficiently, and in true 3D has been a major bottleneck in deriving reliable relationships between altered neuronal function and changes in spine morphology. We introduce a novel system for automated detection, shape analysis and classification of dendritic spines from laser scanning microscopy (LSM) images that directly addresses these limitations. The system is more accurate, and at least an order of magnitude faster, than existing technologies. By operating fully in 3D the algorithm resolves spines that are undetectable with standard two-dimensional (2D) tools. Adaptive local thresholding, voxel clustering and Rayburst Sampling generate a profile of diameter estimates used to classify spines into morphologic types, while minimizing optical smear and quantization artifacts. The technique opens new horizons on the objective evaluation of spine changes with synaptic plasticity, normal development and aging, and with neurodegenerative disorders that impair cognitive function