ZEISS today introduced the Advanced Reconstruction Toolbox for its industry-leading Xradia Versa series of non-destructive 3D X-ray microscopes (XRM) and its Xradia Context 3D X-ray micro-computed tomography (microCT) systems. Leveraging in-house algorithms and proprietary workflows in combination with a high-performance workstation, the Advanced Reconstruction Toolbox dramatically improves the throughput and image quality of 3D image reconstruction — an essential step in 3D XRM for failure analysis (FA). The result is faster time to results, improved FA success rates and even new applications and workflows for semiconductor advanced packaging.
The Advanced Reconstruction Toolbox comprises a workstation and two module offerings — ZEISS OptiRecon for iterative reconstruction, and ZEISS DeepRecon, the first commercially available deep learning reconstruction technology for microscopy applications.
New Reconstruction Techniques Needed3D XRM has become an industry-standard technique for imaging defects to aid root cause investigation of package failures because it uniquely enables visualization of features that are not visible in 2D X-ray projection images. In package FA, both fast results and high FA success rates are important. Consequently, decreasing imaging time while maintaining image quality is of very high value. Typically, Feldkamp-Davis-Kress (FDK) filtered back-projection algorithms are used to reconstruct the 3D dataset from many 2D projections acquired at different sample rotation angles. When image exposure times or numbers of projections are reduced in an effort to improve throughput, the FDK techniques often lead to degraded image quality.
The new ZEISS Advanced Reconstruction Toolbox provides two new advanced reconstruction engines –OptiRecon and DeepRecon — that enable higher scanning speeds while maintaining or even increasing image quality with improved contrast-to-noise ratios for semiconductor advanced packaging failure and structural analysis. In addition to electronics and semiconductor packaging, the Advanced Reconstruction Toolbox can be used for myriad other applications, including materials research, life sciences and advanced battery development.
