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Abstract Three-dimensional microscopy has become an increasingly popular materials characterization technique. This has resulted in a standardized processing scheme for most datasets. Such a scheme has motivated the development of a robust software package capable of performing each stage of post-acquisition processing and analysis. This software has been termed Materials Image Processing and Automated Reconstruction (MIPAR™). Developed in MATLAB™, but deployable as a standalone cross-platform executable, MIPAR™ leverages the power of MATLAB’s matrix processing algorithms and offers a comprehensive graphical software solution to the multitude of 3D characterization problems. MIPAR™ consists of five modules, three of which (Image Processor, Batch Processor, and 3D Toolbox) are required for full 3D characterization. Each module is dedicated to different stages of 3D data processing: alignment, pre-processing, segmentation, visualization, and quantification. With regard to pre-processing, i.e., the raw-intensity-enhancement steps that aid subsequent segmentation, MIPAR’s Image Processor module includes a host of contrast enhancement and noise reduction filters, one of which offers a unique solution to ion-milling-artifact reduction. In the area of segmentation, a methodology has been developed for the optimization of segmentation algorithm parameters, and graphically integrated into the Image Processor. Additionally, a 3D data structure and complementary user interface has been developed which permits the binary segmentation of complex, multi-phase microstructures. This structure has also permitted the integration of 3D EBSD data processing and visualization tools, along with support of additional algorithms for the fusion of multi-modal datasets. Finally, in the important field of quantification, MIPAR™ offers several direct 3D quantification tools across the global, feature-by-feature, and localized classes.
Sosa et al. (Wed,) studied this question.