HS Processing

Image Processing of CR System

The CR System has a variety of image processing capabilities. The existing processing outline is as follows:

• Automatic gradation processing (G processing)
  • Automatically adjust density to be fit for the body part concerned
• Frequency processing (F or HF processing)
  • F processing emphasizes specific fineness.
  • HF processing emphasizes multiple fineness types. HF processing has more variations in emphasis degrees and patterns.
• Equalization processing (E or HE processing)
  • Emphasize the difficult-to-see part.

Konica Minolta provides HF/HE processing called “hybrid processing” as a standard function, which is an upgraded version of conventional frequency processing using multiresolution decomposition. Conventional emphasis processing in CR focused on two points: correcting the image density of the difficult-to-see part and emphasizing image sharpness.

Appearance of New Image Processing

Conventional image processing was outlined on the previous page, and now, image processing capable of improving image speckling (noise) is debuting.

Purposes of Noise Suppression Processing

• Improved images of the body part concerned with distinct noise.
• Improved image quality in low-dose exposure.
• Improved diagnosis capability and suppression of noise to depict borderlines clearly.

New Image Processing (HS Processing)

HS Processing is an image processing method that reduces intrinsic image noise. It is a hybrid processing technology developed to increase image graininess and optimize the balance between contrast and noise in the image at the same time. Decreasing the response of non-edge (noise) components after recognizing edge components in the “multi-resolution decomposition” process of hybrid processing improves image graininess. Now we will explain the details of suppressing noise to improve graininess.

Graininess Improvement Method

Before explaining concrete processing, let’s consider a method to improve graininess.

Hybrid processing (HE/HF processing) uses frequency processing with multi-resolution decomposition that is capable of emphasizing, depending on the degree of detail in a structure (frequency in an image), while HS processing improves graininess by selectively reducing fine noise in an image.

What is multi-resolution decomposition?

In concrete terms, subtracting a smoothed image from the original image as shown in Fig. 2 only generates an image of the edge. Edge images of different degrees of fineness can be obtained by subtraction while changing the smoothing degree at the same time. Eliminating edge images with different degrees of fineness is called multi-resolution decomposition. It is the most basic part of recent image processing in CR and used in various processes. Konica Minolta provides processing using this multi-resolution decomposition as “hybrid processing.”

X-ray pictures copying the human body consist of collective structures with different degrees of fineness, the image can become very clear by extracting the edge part of each fineness (multi-resolution) and adding or subtracting it from the original image as needed.

HS Processing Technology and Principle

The following three processes, known as image speckling, are added to the hybrid processing routine using multi-resolution decomposition, as explained in the previous section, to improve graininess.

1. Edge information extraction
   • Extract edge information from multiple smoothed images and smoothed differential images after multi-resolution decomposition.
2. Selective smoothing
   • Switch smoothing filters based on extracted edge information and retain edge components smoothing only noise components.
3. Density/contrast dependency correction
   • Suppress smoothing of high density/high contrast parts more than smoothed images.

“Retain edge components and smooth only noise components”

By recognizing the structure components as edge structures and applying selective smoothing, signals with reduced noise components are eliminated while retaining structure components.

HS Processing Features

The following three processes known as image speckling are added to the hybrid processing routine using multi-resolution decomposition, as explained in the previous section, to improve graininess.

• Graininess improvement
  • Retain edge components and suppress only granular components.
• Noise/contrast ratio optimization
  • Setting the optimal balance between noise and contrast depending on the diagnostic purposes.
• High compatibility with Regius image processing group
  • More optimization is possible with simultaneous use of other hybrid processing groups (HE or HF).