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A new stationary gridline artifact suppression method based on the 2D discrete wavelet transform.

Hui Tang¹, Dan Tong², Xu Dong Bao²

¹Laboratory of Image Science and Technology, School of Computer Science and Engineering, Southeast University, Nanjing 210096, China; Key Laboratory of Computer Network and Information Integration (Southeast University), Ministry of Education, Nanjing 210000, China; Centre de Recherche en Information Biomédicale sino-français, Laboratoire International Associé, Inserm, Université de Rennes 1, Rennes 35000, France; and Southeast University, Nanjing 210000, China.

Medical Physics

|April 3, 2015

Summary

A new digital radiography method effectively removes stationary antiscatter grid artifacts. This technique preserves crucial image details and offers faster processing compared to existing gridline removal solutions.

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Area of Science:

Medical Imaging
Digital Radiography
Image Processing

Background:

Antiscatter grids in digital x-ray radiography reduce scattered radiation but can cause gridline artifacts when stationary.
Existing gridline removal methods often degrade or lose important image information due to similar spatial frequencies.

Purpose of the Study:

To develop a novel stationary gridline suppression method for digital x-ray images.
To enhance image quality by preserving useful information lost in conventional methods.

Main Methods:

A multiscale 2D discrete wavelet transform recursively decomposes the image.
A gridline detection module identifies subimages with significant gridline signals.
An automatic Gaussian band-stop filter removes gridline signals, followed by inverse wavelet transform for image restoration.

Main Results:

The proposed method efficiently removes gridline signals while preserving image details.
Fourier transform analysis shows superior information preservation compared to existing methods.
The method achieves relatively high performance speed.

Conclusions:

Experimental results confirm the proposed method's efficiency in gridline suppression.
The technique preserves more image information than existing methods within acceptable execution times.