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First installation of AI-based (Intelligent Noise Reduction) software at the equine clinic in Leichlingen

At the end of last year, GIERTH X-Ray international GmbH offered the equine clinic in Leichlingen the option of upgrading their X-ray technology, which they had been using successfully for many years with the detector solution from CANON Medical Components.

For this purpose, a new software version including an AI-based software module (Intelligent Noise Reduction) had to be installed. The aim of this extension was to improve the already very good image quality, especially for the images that represent difficult conditions due to their anatomical size and complexity when depicting different thickness and density structures.

Generally speaking, it can be said that certain equine examinations can only be taken successfully in a special way with a combination of measures and different factors. These include X-ray images of the scull, especially teeth, distal cervical spine, the medio-lateral shoulder joint, the back, knees, chest and pelvis.

With the help of this new software the AI-based "deep learning" function should be able to significantly reduce the noise within the images of the body regions mentioned above, which is always present to a certain amount. Until now, the noise within images has always devalued the diagnostic information.

After the initial months of using this new software, we have reached a highly positive conclusion. It can be stated that with the implementation of these AI-based image processing algorithms, the image quality in the critical regions mentioned above has significantly improved.

Furthermore, as this feature seems to be universally applicable, we have observed a marked enhancement in image quality across all distal limb images. The current X-ray diagnostics are characterized by a highly natural, noise-free presentation and a wide range of grayscale reproduction.

It is safe to say that with the introduction of this new AI-based software, we have succeeded in a further improvement and optimizing the image quality, while at the same time reducing the used X-ray dose. In this respect, we also see it as a contribution to saving X-ray dose with every exposure and eliminating any repeat exposures that may be required.

This has optimized the workflow within the X-ray department of the clinic as well.

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