TY - GEN
T1 - Denoising of low dose CT images using mask non-harmonic analysis with edge-preservation segmentation and whitening filter
AU - Uchikoshi, Kousei
AU - Hasegawa, Masaya
AU - Hirobayashi, Shigeki
N1 - Publisher Copyright:
© COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.
PY - 2019
Y1 - 2019
N2 - Computed tomography (CT) imaging acquires patient images using radiation. However, scanning with high doses of radiation can pose a risk to health, because of radiation hazards. Although the risk to the human body during a CT scan can be reduced by reducing the amount of radiation, the quality of the acquired images may deteriorate. Recently, denoising methods using nonlocal means or block matching and 3D filtering were demonstrated to be effective for denoising CT images. These methods performed denoising by adapting to the noise level, according to the position of the image. However, CT images exhibit different magnitudes of noise at different spatial frequencies, as can be observed in their noise power spectrum. Therefore, a method operating in the frequency space, which can accurately model the CT noise and reduce it effectively, is necessary. In this paper, we present a CT denoising method based on edge-preservation segmentation and denoising using mask nonharmonic analysis (mask NHA). Mask NHA can accurately analyze frequencies with high resolutions when applied to the edge preservation area. By using a whitening filter, we provide noise reduction for specific CT noises and improve the image quality of low-dose CT images. A denoising simulation was performed on a standard-dose CT image to which CT noise was added and the performance of the proposed method was compared to that of conventional methods. The proposed method was found to improve the peak signal-To-noise ratio by 3 to 5 dB, compared to the conventional mask NHA.
AB - Computed tomography (CT) imaging acquires patient images using radiation. However, scanning with high doses of radiation can pose a risk to health, because of radiation hazards. Although the risk to the human body during a CT scan can be reduced by reducing the amount of radiation, the quality of the acquired images may deteriorate. Recently, denoising methods using nonlocal means or block matching and 3D filtering were demonstrated to be effective for denoising CT images. These methods performed denoising by adapting to the noise level, according to the position of the image. However, CT images exhibit different magnitudes of noise at different spatial frequencies, as can be observed in their noise power spectrum. Therefore, a method operating in the frequency space, which can accurately model the CT noise and reduce it effectively, is necessary. In this paper, we present a CT denoising method based on edge-preservation segmentation and denoising using mask nonharmonic analysis (mask NHA). Mask NHA can accurately analyze frequencies with high resolutions when applied to the edge preservation area. By using a whitening filter, we provide noise reduction for specific CT noises and improve the image quality of low-dose CT images. A denoising simulation was performed on a standard-dose CT image to which CT noise was added and the performance of the proposed method was compared to that of conventional methods. The proposed method was found to improve the peak signal-To-noise ratio by 3 to 5 dB, compared to the conventional mask NHA.
KW - Denoising
KW - Edge preservation segmentation
KW - Mask nonharmonic analysis (mask NHA)
KW - Whitening filter
KW - X-ray CT
UR - http://www.scopus.com/inward/record.url?scp=85064839910&partnerID=8YFLogxK
U2 - 10.1117/12.2508202
DO - 10.1117/12.2508202
M3 - 会議への寄与
AN - SCOPUS:85064839910
T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE
BT - Multimodal Biomedical Imaging XIV
A2 - Azar, Fred S.
A2 - Intes, Xavier
A2 - Fang, Qianqian
PB - SPIE
T2 - Multimodal Biomedical Imaging XIV 2019
Y2 - 2 February 2019 through 3 February 2019
ER -