Standardization of Scanning Protocols and Measurements for Additive Manufacturing Quality Assurance

This work is devoted to the (high-throughput) extraction of image biomarkers from acquired, reconstructed, and stored images. The development of new imaging biomarkers involves clearly defined sequential steps. This paper discusses advanced medical imaging data and approaches to processing and optimizing medical imaging data acquisition for accurate, reliable medical models based on real-world data. Segmentation and classification tools provide an approach to feature extraction from images based on nonlinear dynamics methods. In the context of this work, an image is defined as a three-dimensional (3D) set of two-dimensional (2D) digital image fragments. The image fragments are arranged along the Z-axis. Pixels and voxels are represented as rectangles and rectangular parallelepipeds. Pixel and voxel centers coincide with the intersections of a regularly spaced grid. Both views are used in the document. The phase plane method was chosen in this work to analyze 2D imaging. Based on the received metadata, reconstruction is performed using 3D visualization to extract the data of the region of interest. The research results contribute to developing software optimization of medical imaging for additive manufacturing. The issue of harmonizing and standardizing medical image acquisition and reconstruction is being addressed more comprehensively.