X-ray Superresolution via Detector Offset and Affine Transform

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Solution Overview

Problem

Current X-ray diagnostic systems struggle to achieve high-resolution images without significantly increasing the pixel resolution of detectors, which is costly and technically challenging, and existing methods like varying the source-image distance are not feasible with simple systems.

Innovation Solution

A superresolution method is applied by generating a sequence of X-ray images with offset and rotated coordinate systems, using affine 2-D transformations to calculate a high-resolution image, allowing for increased detail visibility without expensive detector upgrades.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If the pixel resolution of the X-ray image detector is increased to achieve high-resolution images, then the image resolution is improved, but the cost and technical complexity of the detector increase significantly

Engineering Contradiction:
Improveimage resolutionVSAvoiddetector complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The patent divides the imaging process into multiple low-resolution images taken at different positions, rather than using a single high-resolution detector. Each image is captured with a standard detector, and the segments (images) are combined through superresolution algorithms to achieve the desired high-resolution output, thereby avoiding the need for an expensive high-resolution detector.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent creates multiple copies of the same anatomical structure at different positions and orientations using a standard detector. These copies are then processed algorithmically to reconstruct a high-resolution image, effectively using multiple low-resolution copies instead of a single high-resolution detector.

Inventive Principle:
Principle #26Copying

2Measurement precision

If the source-image distance is varied to produce sequences of images for superresolution, then the resolution capability is improved, but the system complexity and cost increase

Engineering Contradiction:
Improveresolution capabilityVSAvoidsystem complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The patent introduces dynamic positioning capability to the X-ray system, allowing the detector to be moved to different positions and orientations during image acquisition. This dynamic adjustment enables the capture of multiple images at different geometries, which are then processed to achieve superresolution, without requiring a completely complex system redesign.

Inventive Principle:
Principle #15Dynamics

3Reliability

If a complete X-ray image detector is used for image generation, then the image quality is maintained, but the resolution of anatomical details smaller than the physical resolution capability cannot be shown

Engineering Contradiction:
Improveimage qualityVSAvoiddetail detectability
Core Design Contradiction:
ReliabilityVSMeasurement precision

Solution Approach 1:

The patent merges multiple low-resolution images taken at different positions and orientations into a single high-resolution output image. By combining the information from these multiple images through superresolution algorithms, the system achieves detail detectability beyond the physical resolution capability of individual detectors while maintaining the reliability of standard detector technology.

Inventive Principle:
Principle #5Merging (Combining)

Data Source

PatentUS7817832B2Method for operating an X-ray diagnostic device for the generation of high-resolution images
Publication Date: 2010.10.19 SIEMENS HEALTHINEERS AG
  • US7817832B2 patent drawing
  • US7817832B2 patent drawing
  • US7817832B2 patent drawing

AI summary

The invention relates to a method for operating an X-ray diagnostic device with an X-ray source and an X-ray image detector with a sequence of images of low resolution single pictures with systems of coordinates that are different from each other being created, a harmonization of systems of coordinates of images being carried out, and finally a high resolution image being calculated from the images.