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MODULE 01 — CT RECONSTRUCTION

CT Reconstruction

From analytic to model-based iterative reconstruction — high-speed 3D reconstruction engines,
geometry calibration, and artifact reduction for CBCT, industrial CT, and helical CT.

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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