Gamma Camera Sensitivity Mapping for Sub-Pixel Image Uniformity

Solution Overview

Problem

Gamma cameras exhibit non-uniform spatial response due to sub-pixelation, leading to artifacts in reconstructed images, especially when irradiated by uniform photon flux or influenced by out-of-field radiation sources and detector material defects.

Innovation Solution

A method to determine a spatial sensitivity function by calculating weights for each virtual pixel based on interaction quantities, forming a sensitivity matrix to normalize detected interactions, and reconstructing images using a processing unit to correct non-uniformity.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Device complexity

If sensitivity correction is performed using a single average value for the entire detection surface, then the correction process is simple, but spatial non-uniformity of sensitivity cannot be corrected

Engineering Contradiction:

Improvecorrection process complexityVSAvoidspatial sensitivity uniformity

Core Design Contradiction:

Device complexityVSMeasurement precision

Solution Approach 1:

The detection surface is divided into multiple regions of interest (ROIs), each with its own sensitivity correction value. This segmentation allows the system to account for spatial non-uniformity by treating different areas independently, thereby improving measurement precision across the entire detection surface while maintaining manageable complexity through regional rather than pixel-level correction.

Inventive Principle:

Principle #1Segmentation

2Measurement precision

If sensitivity correction is performed for each pixel individually, then spatial non-uniformity of sensitivity is corrected, but the correction process becomes computationally complex and time-consuming

Engineering Contradiction:

Improvespatial sensitivity uniformityVSAvoidcorrection process complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The detection surface is divided into multiple regions of interest (ROIs), each with its own sensitivity correction value. This segmentation allows the system to account for spatial non-uniformity by treating different areas independently, thereby improving measurement precision across the entire detection surface while maintaining manageable complexity through regional rather than pixel-level correction.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Instead of performing correction for every single pixel, the system applies correction at the regional level. This partial action approach corrects sensitivity non-uniformity sufficiently for medical imaging applications without the excessive computational burden of full pixel-level correction, achieving an optimal balance between precision and complexity.

Inventive Principle:

Principle #16Partial or excessive action

3Measurement precision

If a large number of correction values are stored for different regions, then spatial non-uniformity correction is improved, but memory requirements and data management complexity increase

Engineering Contradiction:

Improvespatial sensitivity uniformityVSAvoidmemory storage requirements

Core Design Contradiction:

Measurement precisionVSQuantity of substance

Solution Approach 1:

The detection surface is divided into multiple regions of interest (ROIs), each with its own sensitivity correction value. This segmentation allows the system to account for spatial non-uniformity by treating different areas independently, thereby improving measurement precision across the entire detection surface while maintaining manageable complexity through regional rather than pixel-level correction.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Instead of performing correction for every single pixel, the system applies correction at the regional level. This partial action approach corrects sensitivity non-uniformity sufficiently for medical imaging applications without the excessive computational burden of full pixel-level correction, achieving an optimal balance between precision and complexity.

Inventive Principle:

Principle #16Partial or excessive action

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

The method reduces spatial non-uniformities in gamma camera response, improving image reconstruction accuracy and reducing artifacts, without requiring homogeneous calibration radiation.

Implementation Method 1

each pixel being configured to form a detection signal upon detection of an interaction of an ionizing photon in the detector material

Methodology Applied

Scientific EffectPhotoelectric effect: Photoelectric Effect

Data Source

PatentEP4361684B1Method for forming gamma image considering spatial non-uniformity of sensitivity

Publication Date: 2026.05.06 COMMISSARIAT A LENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES

Figure 1A~1B
Figure 2A~2B
Figure 2C~2E

AI summary

Method for determining a spatial sensitivity function of a gamma camera, the gamma camera (1) observing an observation field (Ω), which may contain irradiating sources (5), the gamma camera comprising: - a detector material (11); - pixels (12i), distributed over a detection surface (12), each pixel being configured to form a detection signal upon detection of an interaction of an ionizing photon in the detector material; - a sub-pixelization unit (14), programmed to assign a position (x,y) to each detected interaction from detection signals formed by several pixels, the position being determined according to a mesh dividing each pixel (12i) into several virtual pixels (13ij). The method includes steps for determining weights assigned to each virtual pixel, each weight corresponding to a sensitivity of each virtual pixel. Figure 4D.