Image processing and analysis of 3-D microscopy data

While there are many microstructural parameters that can be measured from a planar two-dimensional (2-D) section through a material, there are many measurements that require knowledge of the full three-dimensional (3-D) microstructure, such as true size and shape of individual objects, connectivity and interfacial curvatures. Serial sectioning and reconstruction can reveal the 3-D microstructure but are often considered to be time consuming and labor intensive. However, what is not often realized is that the majority of the time invested in serial sectioning is spent in the image segmentation, wherein individual objects are digitally identified. This article reviews the current state of image segmentation and novel analysis within 3-D materials science. We will also briefly discuss the future possibilities for more efficient segmentation of digital images for a broader range of materials.

[1]  M. Graef,et al.  Application of joint histogram and mutual information to registration and data fusion problems in serial sectioning microstructure studies , 2009 .

[2]  Jeff Simmons,et al.  Three-dimensional analysis of secondary γ′ precipitates in René-88 DT and UMF-20 superalloys , 2009 .

[3]  Somnath Ghosh,et al.  A framework for automated analysis and simulation of 3D polycrystalline microstructures. , 2008 .

[4]  M. Groeber,et al.  Symmetry-based automated extraction of microstructural features: Application to dendritic cores in single-crystal Ni-based superalloys , 2010 .

[5]  P. Voorhees,et al.  Topological complexity and the dynamics of coarsening , 2004, Nature materials.

[6]  M. Graef,et al.  Application and further development of advanced image processing algorithms for automated analysis of serial section image data , 2009 .

[7]  M. Wall,et al.  A high-resolution serial sectioning specimen preparation technique for application to electron backscatter diffraction. , 2001, Ultramicroscopy.

[8]  W. Mullins.  Two‐Dimensional Motion of Idealized Grain Boundaries , 1956 .

[9]  Shijie Wang.  Aqueous lixiviants: Principle, types, and applications , 2007 .

[10]  F. Roters,et al.  Three dimensional investigation of the texture and microstructure below a nanoindent in a Cu single crystal using 3D EBSD and crystal plasticity finite element simulations , 2006 .

[11]  P. Kotula,et al.  Tomographic Spectral Imaging with Multivariate Statistical Analysis: Comprehensive 3D Microanalysis , 2006, Microscopy and Microanalysis.

[12]  Adam Morawiec,et al.  Distribution of grain boundaries in magnesia as a function of five macroscopic parameters , 2004 .

[13]  T. Koga,et al.  Curvature Determination of Spinodal Interface in a Condensed Matter System , 1997 .

[14]  Peter W. Voorhees,et al.  The morphological evolution of dendritic microstructures during coarsening , 2006 .

[15]  Ziji Wu,et al.  Multiple material marching cubes algorithm , 2003 .

[16]  G. Spanos,et al.  Three-dimensional analysis of grain topology and interface curvature in a β-titanium alloy , 2010 .

[17]  John C. Russ,et al.  The Image Processing Handbook , 2016, Microscopy and Microanalysis.

[18]  A. Gokhale,et al.  Effect of gravity on three-dimensional coordination number distribution in liquid phase sintered microstructures , 1999 .

[19]  D. Rowenhorst,et al.  Particle coarsening in high volume fraction solid-liquid mixtures , 2006 .

[20]  G. Shiflet,et al.  Application of Active Contours on Metallurgical Microstructures , 2010 .