Reconstruction Algorithms
An analytic and iterative reconstruction lineup to match image quality and dose requirements.
FDK
Analytic cone-beam reconstruction for circular orbits. Multi-GPU and batch processing deliver high-speed reconstruction of large scans.
SART
Ordered-subset algebraic iterative reconstruction with multi-GPU and multi-pass support.
SIR
Statistical iterative reconstruction (OS-EM family). Stable image quality even under low-dose conditions.
Compressed Sensing
TV-constrained and compressed-sensing reconstruction such as ASD-POCS and ADMM-TV. Preserves edges and suppresses noise in sparse-view, low-dose scans.
Targeted Reconstruction
Multi-resolution iterative reconstruction that reconstructs only the region of interest at high resolution, suppressing truncation artifacts from structures outside the field of view.
MBIR
Model-based iterative reconstruction that accounts for the spectrum, detector response, focal spot size, and gantry motion. The physics model has been quantitatively validated with Monte Carlo simulation.
Scan Type
Scan geometries matched to how your system acquires data.
CBCT
Circular cone-beam scanning. Supports full-scan as well as short-scan, offset-scan, local-scan, and oblique configurations.
Helical CT
Helical scan reconstruction. Cone-parallel rebinning covers continuous scans of long objects.
Tomosynthesis
Supports four tomosynthesis geometries including circular, linear, and isocentric, and lets you configure arbitrary scan geometries directly through the API.
Volume Stitching
Joins and merges volumes from multiple scans to cover large objects beyond a single scan range.
Geometry Calibration
From phantom-based precision calibration to automatic calibration that works from scan data alone.
Offline Calibration
Phantom-based offline geometry calibration. Derives projection offsets, SOD/SDD, and rotation parameters.
Auto Alignment
Automatic alignment that estimates geometric errors from the scan data alone — no phantom required.
Dynamic Online Calibration
Estimates and corrects per-view geometric variation, which differs from scan to scan, directly from the acquired data.
Artifact Reduction
Beam hardening, metal, ring, and scatter — systematic removal of the major artifacts that degrade CT image quality.
Beam Hardening Correction
Single-material beam hardening correction — empirical correction (EBHC) estimated from the image without a phantom, and phantom-based characteristic curve estimation. Supports multi-material (MdBHC) extension.
Streak and Metal Artifact
SMART (Streak and Metal Artifact Reduction Technique) — automatically selects LIMAR or normalized-MAR strategies based on material composition and runs BHC in a single pipeline.
Ring Artifact Reduction
Ring artifact removal in both the sinogram domain and the reconstructed image domain.
Scatter Correction
Kernel-based scatter estimation and removal — estimates the scatter distribution from projection images alone, with no extra hardware, and removes it iteratively.
Detector Corrections
Corrections for detector lag, bad pixels, and photon starvation.
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