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About this Abstract
Meeting 2027 TMS Annual Meeting & Exhibition
Symposium Algorithms Development in Materials Science and Engineering
Presentation Title MISalign: Human-in-the-loop Image Alignment and Blending for Communication and Computation
Author(s) Jessica Garnett, Ji-Cheng Zhao
On-Site Speaker (Planned) Jessica Garnett
Abstract Scope MISalign is an open-source python package that combines multiple manual and automated image alignment techniques with both unblended and blended image montage rendering. Montaging microscope images is useful for qualitative communication, especially of location-based features such as appear in additive manufacturing or composition gradient experiments. It is also useful for quantitative analysis, as it allows the fusion of coordinate systems from many images which is particularly valuable in shallow composition gradient experiments. These fused single-mode coordinate systems can also be aligned on one another to enable multi-modal data fusion across length scales, such as combining many high resolution SEM images with low resolution large area EDS. MISalign also adopts FAIR data practices as it saves alignment information to JSON and can work with both standard image files as well as HDF5 datasets such as those produced by Dream3D or Nexus format specifications.
Proceedings Inclusion? Planned:
Keywords Characterization,

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