Cone Beam Reconstruction

The Cone Beam Reconstruction plugin reconstructs 3D volumetric images from cone-beam computed tomography (CBCT) projection data. Using filtered back-projection algorithms, it transforms a series of 2D X-ray projections acquired at different angles into a complete 3D volume representation of the scanned object.

Overview

Cone-beam CT differs from conventional fan-beam CT by using a cone-shaped X-ray beam that illuminates a 2D detector panel, enabling faster acquisition of volumetric data. This geometry is common in:

• Industrial CT: Non-destructive testing, metrology, quality inspection
• Dental CBCT: Maxillofacial imaging, implant planning
• Micro-CT: Small animal imaging, materials research
• C-arm systems: Interventional radiology, surgical guidance

The plugin implements the Feldkamp-Davis-Kress (FDK) algorithm with configurable geometry parameters, filtering options, and post-processing controls to optimize reconstruction quality for your specific imaging setup.

Accessing the Plugin

1. Navigate to the Advanced ribbon tab
2. Click Cone Beam Reconstruction in the Plugins section
3. The reconstruction controls panel opens in the task dock

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Input Projections

The plugin supports two sources for projection data:

Source	Description
Active Volume	Use the currently loaded volume object as input projections. The volume should contain the projection stack with each slice representing one projection image.
From Disk	Import projection images directly from files. Opens a file selection dialog to choose multiple image files representing the projection series.

When selecting From Disk, a file manager dialog appears where you can:

• Select multiple projection image files
• Configure axis inversion (X, Y, Z) if projections need reorientation
• Apply intensity inversion if contrast is reversed

The line edit below the dropdown displays the number of selected files and their directory location.

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Common Parameters

These fundamental geometry parameters define the cone-beam CT acquisition setup:

Parameter	Description	Default
Distance from source to detector (mm)	Distance from the X-ray source to the detector plane. Affects magnification and geometry of the scan.	815.19
Distance from source to object (mm)	Distance from the X-ray source to the object isocenter (rotation axis). Defines the radius of the scan trajectory.	153.48
Detector pixel size X (mm)	Physical size of a detector pixel along the horizontal axis.	0.4
Detector pixel size Y (mm)	Physical size of a detector pixel along the vertical axis.	0.4
X-ray scan start angle (°)	Starting angle of the X-ray scan. Defines the initial gantry position.	0
X-ray scan total angle (°)	Total angular range covered by the scan. Use 360° for a full scan, less for short-scan acquisitions.	360
Rotation direction	Direction of gantry rotation during acquisition: Clockwise or Anti-clockwise.	Anti-clockwise

Geometry Parameters

These values should match your scanner's physical configuration. Consult your scanner documentation or calibration data for accurate geometry parameters. Incorrect values will result in blurred or distorted reconstructions.

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Projection Parameters

Advanced parameters for correcting detector and source misalignments. These are collapsed by default and only needed when fine-tuning reconstruction quality.

Detector Offsets

Parameter	Description	Default
Detector center offset horizontal (mm)	Horizontal offset of the detector center relative to the rotation axis. Use to correct for detector misalignment.	0
Detector center offset vertical (mm)	Vertical offset of the detector center relative to the rotation axis. Use to correct for detector misalignment.	0

Source Offsets

Parameter	Description	Default
Source center offset horizontal (mm)	Horizontal offset of the X-ray source relative to the rotation axis.	0
Source center offset vertical (mm)	Vertical offset of the X-ray source relative to the rotation axis.	0

Detector Tilt Angles

Parameter	Description	Default
Out of plane angle (°)	Rotation of the detector around the X axis (out-of-plane tilt). Use to correct for detector tilt.	0
In plane angle (°)	Rotation of the detector around the Z axis (in-plane tilt). Use to correct for detector tilt.	0

Displaced Detector

Enable this option when using off-centered (displaced) detector panels, common in short-scan acquisitions or systems designed to extend the effective field of view.

Parameter	Description	Default
Enable displaced detector	Activate special handling for off-centered detector panels.	Off
Angular gap threshold (°)	Angular gap threshold for detecting short scans with displaced detectors. Above this value, short-scan weighting is applied.	20

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Preprocessing Parameters

Preprocessing operations applied to projection images before reconstruction. These filters can improve image quality and reduce artifacts. The preprocessing pipeline follows a specific order optimized for CBCT best practices.

Preprocessing Order

The preprocessing steps are applied in a carefully optimized sequence: (1) Intensity offset correction → (2) Intensity normalization → (3) Speckle removal → (4) Ring artifact reduction → (5) Projection smoothing → (6) Scatter correction → (7) Flat-field correction → (8) Logarithm conversion → (9) Beam hardening correction. This order ensures each filter works on appropriately prepared data.

Projection Skip

Parameter	Description	Range	Default
Projection skip	Number of projections to skip between used projections. 0 uses all projections, 1 uses every 2nd projection, 2 uses every 3rd, etc.	0+	0

Testing Only

Projection skip is intended for testing and parameter tuning only. While it significantly speeds up reconstruction by reducing the number of projections processed, it also reduces angular sampling and degrades reconstruction quality. Skipping projections introduces undersampling artifacts, including streaks and loss of fine detail.

Use cases:

• Quick parameter previews during workflow development
• Fast iteration when tuning geometry or filter settings
• Preliminary reconstructions on large datasets

Do NOT use projection skip for final production reconstructions. Always use all available projections (skip = 0) for clinical, quality inspection, or publication-quality results.

Projection Smoothing

Parameter	Description	Options	Default
Smoothing level	Apply smoothing to projection images before reconstruction. Reduces high-frequency noise while attempting to preserve edges.	Off, Low, Medium, High	Off

• Off: No smoothing applied
• Low: Light smoothing – recommended for most cases
• Medium: Moderate smoothing – good balance for noisy data
• High: Strong smoothing – maximum noise reduction but may soften details

Smoothing vs. Noise

Smoothing reduces noise but can blur fine structures. Start with Low or Medium settings. If you need heavy smoothing, consider whether your acquisition parameters (exposure time, detector gain) can be improved to reduce noise at the source.

Intensity Normalization

Parameter	Description	Options	Default
Normalization mode	Normalize projection intensities for consistent attenuation values across the dataset.	Off, Maximum, Air Peak, Fixed	Off

• Off: No normalization applied
• Maximum: Scale all projections to the maximum intensity value found
• Air Peak: Automatically detect the air region intensity peak for normalization
• Fixed: Use a user-specified relative position (0.0–1.0) for normalization

Parameter	Description	Range	Default
Relative air peak position	When using Fixed normalization mode, specifies the relative position in the intensity histogram to use as the air reference.	0.0–1.0	0.9

When to Normalize

Intensity normalization is useful when projections have varying brightness levels due to source fluctuations, detector drift, or inconsistent acquisition settings. It ensures uniform attenuation scaling across all projections.

Speckle Removal

Parameter	Description	Options	Default
Speckle removal	Remove isolated detector defects (hot/dead pixels) that appear as bright or dark spots in projections.	Off, Single Pixel, Multi Pixel	Off

• Off: No speckle removal
• Single Pixel: Strict mode – removes only extreme single-pixel outliers
• Multi Pixel: Relaxed mode – handles larger defective pixel regions

Detector Calibration

Speckle removal is a corrective filter for defective detector pixels. For best results, use proper detector calibration (flat-field correction) to prevent systematic defects. Speckle removal should be used as a supplement, not a replacement, for good calibration.

Ring Artifact Reduction

Parameter	Description	Options	Default
Ring artifact reduction	Reduce concentric ring artifacts caused by systematic detector pixel variations. These appear as circles centered on the rotation axis.	Off, Low, Medium, High	Off

• Off: No ring artifact reduction
• Low: Light correction for minor rings
• Medium: Moderate correction for typical ring artifacts
• High: Strong correction for severe ring artifacts

Ring Artifacts

Ring artifacts occur when detector pixels have non-uniform gain or offset, creating circular patterns in the reconstruction. Higher correction levels suppress rings more strongly but may introduce slight blurring. Start with Low or Medium.

Beam Hardening Correction

Parameter	Description	Options	Default
Beam hardening preset	Correct cupping artifacts from polychromatic X-ray beam hardening. Lower-energy photons are absorbed more in outer regions, making the center appear brighter (cupping).	Off, Low, Medium, High	Off

• Off: No beam hardening correction
• Low: Light polynomial correction for mild cupping
• Medium: Moderate correction for typical cupping artifacts
• High: Strong correction for severe cupping (thick or high-Z materials)

Beam Hardening Physics

Beam hardening is a physical phenomenon in polychromatic X-ray imaging. As the X-ray beam passes through the object, lower-energy photons are preferentially absorbed, "hardening" the beam (increasing average energy). This causes non-linear attenuation and cupping artifacts. Beam hardening correction applies polynomial compensation based on water-equivalent thickness.

Logarithm Conversion

Parameter	Description	Default
Enable logarithm conversion	Convert raw detector intensities to attenuation values using logarithmic transformation: attenuation = -log(I / I0).	On

Enable this if your projections are raw transmission values (detector intensity measurements). Disable if projections are already logarithmized attenuation data.

Raw vs. Attenuation Data

Most CBCT systems output raw detector intensities (I), which must be converted to attenuation values (-log(I/I0)) for reconstruction. If your data is already preprocessed as attenuation or "sinogram" data, disable this option to avoid double logarithm.

Scatter Correction

Enable scatter correction to reduce contrast loss and cupping caused by scattered X-ray radiation.

Parameter	Description	Default
Enable scatter correction	Apply scatter radiation correction. X-ray scatter adds background signal that degrades image quality.	Off

Parameter	Description	Range	Default
Scatter air threshold	Detector value threshold for identifying air regions. Pixels above this value are considered air for scatter estimation.	0–65535	32000
Scatter-to-primary ratio	Estimated ratio of scatter to primary radiation. Depends on object size and beam energy.	0.0–0.3	0.0

Advanced Parameter

Scatter correction requires careful tuning of the air threshold and scatter-to-primary ratio. Incorrect values can introduce artifacts. Typical scatter-to-primary ratios range from 0.02 (small objects, high energy) to 0.15 (large objects, low energy). Start with conservative values and increase gradually.

Intensity Offset Correction

Parameter	Description	Default
Enable intensity offset correction	Subtract a constant offset/bias from all projection intensities (percentage of maximum detector intensity).	Off

Parameter	Description	Range	Default
Intensity offset bias (%)	Percentage of maximum intensity to subtract from projections. Typical starting values: 0.5–2.0%. Higher values (up to 5%) may be used but can cause negative intensities and streak artifacts.	0.0–100.0	0.0

This correction removes DC offsets in detector readings (e.g., from dark current or electronic bias). Use small values and inspect reconstructions; if streaks or negative values appear, reduce the bias.

Intensity Offset Precautions

Too large an offset bias can introduce negative intensities and streak artifacts in the reconstruction. Start with 0.5–2% and increase slowly while monitoring results. Prefer detector calibration (flat-field correction) over using large offset biases.

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Flat-field Correction

Flat-field correction removes systematic detector artifacts using calibration images. This normalizes detector response across all pixels, compensating for gain variations and fixed-pattern noise.

Calibration Images Required

Flat-field correction requires two calibration images:

• Dark Field: Detector response with no X-ray exposure (captures dark current and fixed noise)
• Bright Field: Detector response to uniform X-ray illumination without any object (captures pixel-wise gain variations)

Corrected projection = (Raw - Dark) / (Bright - Dark)

Parameter	Description	Format
Dark field image path	Path to the dark field calibration image.	Image file (TIFF, PNG, etc.)
Bright field image path	Path to the bright field (flat field) calibration image.	Image file (TIFF, PNG, etc.)

Flat-field images should match the resolution and bit depth of your projection images. The correction is applied after scatter correction and before logarithmic conversion.

Acquisition Best Practice

Acquire dark field and bright field images using the same detector settings (gain, exposure time) as your projection data. Re-acquire calibration images periodically to account for detector drift over time.

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Reconstruction Parameters

Filter settings that control the reconstruction algorithm behavior:

Parameter	Description	Range	Default
Truncation correction	Correction factor for truncated projections where the object extends beyond the detector field of view. Values above 0 enable correction.	0.0–1.5	1.0
Cut frequency	Hann filter cut frequency. Higher values preserve more high-frequency detail (sharper but noisier), lower values increase smoothing (softer but cleaner). Set to 0 to disable the Hann filter.	0.0–1.5	0.0

Truncation Correction

When the scanned object is larger than the detector's field of view, projections become truncated at the edges. This causes cupping artifacts and intensity errors in the reconstruction. The truncation correction parameter helps mitigate these effects by extrapolating the missing data.

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Result Parameters

Post-processing options applied to the reconstructed volume:

Intensity and Cropping

Parameter	Description	Default
Auto invert intensity	Automatically invert the intensity of the reconstructed image. Enable if the reconstructed object appears with reversed contrast (bright areas appear dark).	On
Auto crop	Automatically crop the reconstructed volume to remove empty background regions, resulting in a tighter bounding box around the object.	On
Crop margin	Margin in pixels to preserve around the cropped object. Only applies when auto crop is enabled.	10

Intensity Clamping

Clamp reconstructed intensity values to remove outliers. This is useful for eliminating extreme values that can distort the histogram and reduce contrast in the displayed image.

Why Clamp Intensities?

Reconstruction artifacts, noise, or metal objects can produce extreme intensity values (very bright or very dark voxels). These outliers compress the useful intensity range in the histogram, reducing visible contrast. Clamping removes these extremes while preserving the main tissue/material distribution.

Low Clamping

Parameter	Description	Default
Enable low clamping	Enable clamping of values below the specified threshold. Values below the threshold are set to the threshold value.	Off
Low clamping type	Absolute: Threshold is a fixed intensity value. Percental: Threshold is a percentage of the data range from minimum.	Absolute
Low clamping value	Threshold value. In Absolute mode, this is the actual intensity cutoff. In Percental mode, this is the percentage of the intensity range from minimum (0% = minimum, 100% = maximum).	0.0

Typical use: Clamp negative values or background noise to zero. For example, set type to Absolute and value to 0.0 to remove all negative intensities.

High Clamping

Parameter	Description	Default
Enable high clamping	Enable clamping of values above the specified threshold. Values above the threshold are set to the threshold value.	Off
High clamping type	Absolute: Threshold is a fixed intensity value. Percental: Threshold is a percentage of the data range from maximum.	Percental
High clamping value	Threshold value. In Absolute mode, this is the actual intensity cutoff. In Percental mode, this is the percentage of outlier values to clamp (e.g., 0.001% removes the brightest 0.001% of voxels).	0.001

Typical use: Remove bright artifacts or saturated regions. For example, set type to Percental and value to 0.001 to clamp the brightest 0.001% of voxels.

Clamping Strategy

Start with high clamping in Percental mode (0.001–0.01%) to remove bright outliers. This often provides the most noticeable improvement in display contrast. Use low clamping in Absolute mode only if you observe significant negative values or dark artifacts.

Sharpening

Optional Unsharp Mask (USM) sharpening to enhance edge contrast and local detail in the reconstruction. Enable the Sharpening checkbox to activate these controls.

Parameter	Description	Range	Default
Enable sharpening	Enable Unsharp Mask (USM) sharpening on the reconstructed volume. Sharpening can enhance edge contrast and local detail but may amplify noise.	-	On
Iterations	Number of times the sharpening operation is applied. More iterations increase sharpening strength but also processing time.	1+	2
Radius (pixels)	Radius of the local neighborhood used for sharpening. Larger radius affects broader features, smaller radius affects fine details.	1+	3
Contrast (%)	Sharpening amount expressed as a percentage. Higher values produce stronger sharpening.	1–200	50

Sharpening and Noise

Sharpening enhances edges but also amplifies noise. Use conservative settings (low contrast %, few iterations) for noisy data, or disable sharpening entirely and apply noise reduction before sharpening in a separate processing step. Over-sharpening can create "halo" artifacts around edges.

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Running Reconstruction

1. Configure input: Select the projection source (Active Volume or From Disk)
2. Set geometry parameters: Enter your scanner's geometry values in the Common Parameters section
3. Configure preprocessing (optional): Expand Preprocessing Parameters to apply filters (smoothing, artifact reduction, beam hardening correction, etc.)
4. Adjust advanced settings (optional): Expand Projection Parameters and Reconstruction Parameters for fine-tuning
5. Configure output options: Set Result Parameters for intensity clamping, cropping, and sharpening preferences
6. Click Reconstruct: The reconstruction process begins with a progress dialog

The reconstructed volume is automatically added to the project with a name derived from the input source (e.g., "OriginalName (Reconstructed)").

Recommended Workflow

For a typical first reconstruction:

1. Use default settings (no preprocessing)
2. Check the result quality
3. If artifacts are present, enable specific preprocessing filters one at a time
4. Use projection skip (e.g., skip=3) for fast parameter testing, then set skip=0 for final reconstruction

Reset to Default

Click Reset to Default to restore all parameters to their factory default values. This is useful when starting a new reconstruction workflow or troubleshooting unexpected results.

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Workflow Examples

Example 1: Basic Reconstruction from Projection Files

1. Click Cone Beam Reconstruction in the Advanced tab
2. Select From Disk in the Projections dropdown
3. In the file dialog, select all projection images (e.g., TIFF or DICOM series)
4. Configure axis inversion if needed (check preview to verify orientation)
5. Enter your scanner geometry:
   • Source-to-detector distance
   • Source-to-object distance
   • Detector pixel size
   • Scan angles and rotation direction
6. Leave Preprocessing Parameters at defaults for first attempt
7. Leave Projection Parameters at defaults unless you know your system has misalignments
8. Enable Auto crop and Auto invert intensity in Result Parameters
9. Enable High clamping (Percental, 0.001%) to remove bright outliers
10. Click Reconstruct
11. Review the reconstructed volume in the 3D view

Example 2: High-Quality Reconstruction with Preprocessing

Use this workflow when you need maximum quality and artifact suppression:

1. Load projections (Active Volume or From Disk)
2. Configure geometry parameters
3. Enable preprocessing filters:
   • Projection smoothing: Low or Medium (for noise reduction)
   • Intensity normalization: Air Peak (for consistent attenuation)
   • Speckle removal: Single Pixel (for isolated defects)
   • Ring artifact reduction: Low or Medium (if rings are visible)
   • Beam hardening correction: Medium (for typical cupping)
   • Enable logarithm conversion: On (for raw detector data)
4. Configure flat-field correction (if calibration images available):
   • Select dark field image
   • Select bright field image
5. Set reconstruction parameters:
   • Truncation correction: 1.0
   • Hann cut frequency: 0.5 (moderate smoothing)
6. Configure result parameters:
   • Auto invert intensity: On
   • Auto crop: On
   • High clamping: Percental, 0.001%
   • Sharpening: On (Iterations=2, Radius=3, Contrast=50%)
7. Click Reconstruct

Processing Time

Enabling multiple preprocessing filters increases reconstruction time. Use projection skip for parameter testing, then disable it (skip=0) for the final production reconstruction.

Example 3: Fast Parameter Testing

When testing geometry or filter parameters on large datasets:

1. Set Projection skip to 3 or 5 (uses every 4th or 6th projection)
2. Disable Auto crop for faster processing
3. Disable Sharpening for faster processing
4. Run reconstruction and check result quality
5. Adjust parameters as needed
6. For final reconstruction: Set projection skip back to 0 and re-enable desired post-processing

Final Production Reconstruction

Always set projection skip to 0 for final reconstructions used in analysis, publication, or quality control. Skipped projections reduce angular sampling and introduce artifacts.

Example 4: Reconstructing from Loaded Volume Stack

1. Load the projection stack as a volume (File → Import)
2. Ensure the projection volume is the active volume
3. Click Cone Beam Reconstruction
4. Select Active Volume as the projection source
5. Enter geometry parameters
6. Click Reconstruct

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Technical Background

Feldkamp-Davis-Kress (FDK) Algorithm

The plugin implements the FDK algorithm, the standard filtered back-projection method for cone-beam CT reconstruction. The algorithm:

1. Pre-weights each projection by the cosine of the cone angle
2. Filters projections row-by-row using a ramp filter (optionally windowed with Hann or other filters)
3. Back-projects filtered data along ray paths through the reconstruction volume

The FDK algorithm provides good image quality for circular scan trajectories when the cone angle is moderate. For very large cone angles or helical trajectories, more advanced algorithms may be required.

Geometry Conventions

The plugin uses standard cone-beam CT geometry conventions:

• Source: Point X-ray source emitting a cone-shaped beam
• Detector: Flat-panel detector perpendicular to the central ray
• Rotation axis: Vertical axis (Y) passing through the isocenter
• Angles: Measured from the initial gantry position, positive in the rotation direction

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Troubleshooting

Blurred or Smeared Reconstruction

Possible causes:

• Incorrect geometry parameters (distances, pixel size)
• Wrong rotation direction (clockwise vs. anti-clockwise)
• Projection offsets not properly configured

Solutions:

• Verify geometry parameters match your scanner calibration data
• Check rotation direction and flip if necessary
• Verify projection offsets (detector center horizontal/vertical)
• Reduce Hann cut frequency for smoother reconstruction (reduces noise but softens edges)

Ring Artifacts (Concentric Circles)

Cause: Detector pixel defects or gain variations create systematic errors that appear as rings centered on the rotation axis.

Solutions:

• Enable Ring artifact reduction (start with Low or Medium)
• Use Flat-field correction with properly acquired dark/bright field calibration images
• Enable Speckle removal (Single Pixel mode) to remove isolated defective pixels
• Check detector calibration – re-calibrate if rings persist

Best Practice

Ring artifacts are best prevented through proper detector calibration. Flat-field correction is the most effective solution. Ring artifact reduction filter is a corrective measure when calibration data is unavailable.

Cupping Artifacts (Brighter Center)

Cause: Polychromatic beam hardening – lower-energy X-rays are absorbed more in outer regions, making the center appear brighter.

Solutions:

• Enable Beam hardening correction (start with Medium preset)
• If cupping is severe, increase to High preset
• Verify truncation correction is enabled if object extends beyond field of view
• For very thick or high-Z materials, custom beam hardening coefficients may be needed

When Cupping is Normal

Some cupping may be normal for objects with varying density. Only apply beam hardening correction if the cupping is an artifact (e.g., uniform materials appearing non-uniform).

Streaking Artifacts

Possible causes:

• Insufficient angular sampling (too few projections or excessive projection skip)
• Highly attenuating materials (metal) creating photon starvation
• Detector saturation or clipping

Solutions:

• Disable or reduce Projection skip (set to 0 for full angular sampling)
• Increase number of acquired projections if possible
• Enable Scatter correction if scatter is significant
• Use High clamping to remove extreme bright values from metal artifacts
• Adjust acquisition parameters (exposure time, beam energy) if detector is saturating

Projection Skip Artifacts

Projection skip reduces angular sampling, which can cause streaking. Never use projection skip values > 0 for final reconstructions.

Noisy Reconstruction

Cause: Low X-ray dose, high detector noise, or insufficient projection counts.

Solutions:

• Enable Projection smoothing (Low or Medium)
• Increase Hann cut frequency for more filtering (lower values = smoother)
• Disable Sharpening (sharpening amplifies noise)
• If possible, increase acquisition dose or detector exposure time
• Apply denoising filters after reconstruction (separate processing step)

Reversed Contrast (Dark Object on Bright Background)

Cause: Intensity inversion during acquisition or preprocessing.

Solutions:

• Enable Auto invert intensity in Result Parameters
• Check Invert intensity option in input projection settings (From Disk mode)
• Verify logarithm conversion is correctly enabled/disabled based on data type

Reconstruction Too Dark or Bright

Possible causes:

• Histogram outliers compressing useful intensity range
• Incorrect window/level settings in viewer

Solutions:

• Enable High clamping (Percental, 0.001–0.01%) to remove bright outliers
• Enable Low clamping (Absolute, 0.0) to clamp negative values
• Adjust window/level after reconstruction using the Image tab tools
• Check that projection data has appropriate dynamic range

Flat or Low Contrast Result

Cause: Extreme intensity values compressing the useful data range.

Solutions:

• Enable Intensity clamping (both low and high)
• Use Percental high clamping at 0.001–0.01% to remove the brightest outliers
• Adjust window/level in the image viewer
• Check histogram to identify outliers

Speckled or "Salt and Pepper" Noise

Cause: Isolated detector defects (hot pixels, dead pixels).

Solutions:

• Enable Speckle removal (Single Pixel or Multi Pixel mode)
• Use Flat-field correction to calibrate detector response
• Increase speckle threshold multiplier if too many good pixels are being removed

Missing or Truncated Object Regions

Cause: Object extends beyond detector field of view, causing projection truncation.

Solutions:

• Increase Truncation correction parameter (values > 1.0)
• Verify detector is properly positioned to capture the full object
• Check projection offsets (detector center horizontal/vertical)
• Consider using displaced detector mode if appropriate for your geometry

Truncation Limits

Truncation correction can only compensate for moderate truncation. If large portions of the object extend beyond the detector, reconstruction quality will be limited. The best solution is to reposition the detector or reduce magnification.

Reconstruction Fails or Crashes

Possible causes:

• Insufficient memory for large datasets
• Incompatible projection data format
• Geometry parameter errors (e.g., source distance = 0)

Solutions:

• Enable Projection skip to reduce memory usage (for testing only)
• Verify all geometry parameters are non-zero and physically reasonable
• Check projection image format and bit depth
• Close other applications to free memory
• For very large datasets, use a workstation with more RAM

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Scripting API

The cone beam reconstruction functionality is fully exposed through the scripting API, allowing automated batch processing and integration into custom workflows.

Python Example

import ScriptingApi as api
import os

app = api.Application()
volume_operations = app.get_volume_operations()

# Helper function to create file paths with zero-padded numbering
def create_file_paths(directory, prefix, start, end, num_zeros, extension='.tif'):
    file_paths = []
    for i in range(start, end + 1):
        padded_number = str(i).zfill(num_zeros)
        filename = f"{prefix}{padded_number}{extension}"
        full_path = os.path.join(directory, filename)
        file_paths.append(full_path)
    return file_paths

projection_files = create_file_paths(
    directory="C:/Data/Projections",
    prefix="XYZ_Object",
    start=100001,
    end=100999,
    num_zeros=6
)

# Create reconstruction settings
cone_beam_reconstruction_settings = api.ConeBeamReconstructionSettings()

# Reconstruct from projection files on disk
reconstructed_volume = volume_operations.reconstruct_volume_using_cone_beam_reconstruction(
    "",                                       # volumeName: empty string when using files
    projection_files,                         # fileNames: list of projection file paths
    cone_beam_reconstruction_settings         # reconstruction parameters
)

print(f"Reconstructed volume from files: {reconstructed_volume}")

Enum Types

The scripting API provides type-safe enums for all preprocessing modes:

Enum Type	Values	Description
api.CBR_ProjectionSmoothingLevel.Off	Off, Low, Medium, High	Projection smoothing intensity
api.CBR_IntensityNormalizationMode.Off	Off, Maximum, AirPeak, Fixed	Intensity normalization method
api.CBR_SpeckleRemovalMode.Off	Off, SinglePixel, MultiPixel	Speckle removal strategy
api.CBR_RingArtifactReductionLevel.Off	Off, Low, Medium, High	Ring artifact correction strength
api.CBR_BeamHardeningPreset.Off	Off, Low, Medium, High	Beam hardening correction preset
api.CBR_ClampingType.Absolute	Absolute, Percental	Intensity clamping type

Batch Processing Example

Automation Benefits

Using the scripting API enables:

• Batch processing of multiple datasets with identical parameters
• Integration into automated QA/QC pipelines
• Reproducible reconstructions with version-controlled parameter sets
• Custom preprocessing workflows not available in the GUI

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Best Practices and Recommendations

Acquisition Guidelines

1. Projection count: Use at least 360–720 projections for a full 360° scan. More projections improve angular sampling and reduce streaking.
2. Detector calibration: Acquire dark and bright field images regularly for flat-field correction.
3. Exposure settings: Balance dose, noise, and acquisition time. Higher dose reduces noise but increases scan time.
4. Geometric accuracy: Calibrate scanner geometry periodically to ensure accurate distance and offset parameters.

Parameter Selection

1. Start simple: Begin with default parameters and enable preprocessing only as needed.
2. Enable one filter at a time: When troubleshooting artifacts, enable preprocessing filters individually to identify the most effective corrections.
3. Use projection skip for testing only: Set projection skip to 3–5 for fast parameter testing, then always set to 0 for final reconstructions.
4. Balance smoothing and detail: Low or Medium smoothing levels preserve detail while reducing noise. Avoid High unless noise is severe.
5. Tune clamping carefully: Use Percental high clamping at 0.001–0.01% to remove bright outliers without affecting the bulk of the data.

Quality Control

1. Visual inspection: Check for rings, cupping, streaks, and noise in reconstructed slices.
2. Histogram analysis: Examine the intensity histogram for outliers or unexpected distributions.
3. Quantitative metrics: If available, compare reconstructed values to known reference materials or calibration phantoms.
4. Consistency: Use identical parameters for datasets that will be compared quantitatively.

Optimization for Large Datasets

1. Memory management: Large reconstructions (> 2000³ voxels) require significant RAM. Close unnecessary applications.
2. Test first: Use projection skip for initial parameter tuning, then run full reconstruction overnight.
3. Incremental processing: For very large datasets, consider splitting into smaller angular ranges and combining afterward.
4. Parallel processing: The reconstruction algorithm uses multi-threading. Ensure adequate CPU cores are available.

Performance Tip

Reconstruction time scales with the number of projections, voxel count, and enabled preprocessing filters. A typical 1000³ voxel reconstruction from 720 projections takes 3–10 minutes on a modern workstation, depending on preprocessing complexity.

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Related Topics

• Plugins Overview
• Advanced Tab Overview
• Volume Import