Analysis on Optimal Approach of Blind Deconvolution Algorithm in Chest CT Imaging

• 발행기관: 대한방사선과학회(구 대한방사선기술학회)
• 저자명: 이영준(Young-Jun Lee) 민정환(Jung-Whan Min)
• 간행물 정보: 『방사선기술과학』방사선기술과학 제45권 제2호, 145~150쪽, 전체 6쪽
• 주제분류: 의약학 > 방사선과학
• 파일형태: PDF
• 발행일자: 2022.04.30

영문 초록

The main purpose of this work was to restore the blurry chest CT images by applying a blind deconvolution algorithm. In general, image restoration is the procedure of improving the degraded image to get the true or original image. In this regard, we focused on a blind deblurring approach with chest CT imaging by using digital image processing in MATLAB, which the blind deconvolution technique performed without any whole knowledge or information as to the fundamental point spread function (PSF). For our approach, we acquired 30 chest CT images from the public source and applied three type’s PSFs for finding the true image and the original PSF. The observed image might be convolved with an isotropic gaussian PSF or motion blurring PSF and the original image. The PSFs are assumed as a black box, hence restoring the image is called blind deconvolution. For the 30 iteration times, we analyzed diverse sizes of the PSF and tried to approximate the true PSF and the original image. For improving the ringing effect, we employed the weighted function by using the sobel filter. The results was compared with the three criteria including mean squared error (MSE), root mean squared error (RMSE) and peak signal-to-noise ratio (PSNR), which all values of the optimal-sized image outperformed those that the other reconstructed two-sized images. Therefore, we improved the blurring chest CT image by using the blind deconvolutin algorithm for optimal approach.

목차

Ⅰ. Introduction

Ⅱ. Material & Method

Ⅲ. Result & Discussion

Ⅳ. Conclusion

REFERENCES

키워드

블라인드 디블러링 디컨볼루션 흉부 컴퓨터단층촬영 영상 가우시안 잡음 점확산함수 Blind Deblurring Deconvolution Chest CT Imaging Gaussian Blurring Point Spread Function (PSF)