Low Dose SPECT Image Denoising Using a Generative Adversarial Network

UM > Faculty of Science and Technology > DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING

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	Low Dose SPECT Image Denoising Using a Generative Adversarial Network
	Zhang, Q; Sun, JZ; Mok, S. P.
	2019-07-01
Source Publication	2019 International Conference on Medical Imaging with Deep Learning
Abstract	The image noise level and resolution of SPECT images are relatively poor attributed to the limited number of detected counts and various physical degradation factors during acquisitions. This study aims to apply and evaluate the use of generative adversarial network (GAN) method in static SPECT image denoising. A population of 4D extended cardiac-torso (XCAT) phantoms were used to simulate 10 male and female patients with different organ sizes and activity uptakes. An analytical projector was applied to simulate 120 projections from right anterior oblique to left posterior oblique positions with two noise levels. The first noise level was based on a standard clinical count rate of 987 MBq injection and 16 min acquisition (low noise) while the other was 1/8 of the previous count rate (high noise). The high noise and low noise SPECT reconstructed images of 9 patients, i.e., 1026 images (9×114 axial slices) respectively, were paired for training. High noise SPECT images of 1 patient were tested using the trained GAN. The noise level is substantially reduced in high noise SPECT reconstructed images after using the GAN. Our method has the potential to decrease the noise level of SPECT images, which could be traded for a reduced injection dose or acquisition time while still maintaining the similar image quality as compared to the original low noise images for clinical diagnosis.
Keyword	Image denoising Generative adversarial network SPECT
URL	View the original
Language	英語English
The Source to Article	PB_Publication
PUB ID	47959
Document Type	Conference paper
Collection	DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING
Corresponding Author	Mok, S. P.
Recommended Citation GB/T 7714	Zhang, Q,Sun, JZ,Mok, S. P.. Low Dose SPECT Image Denoising Using a Generative Adversarial Network[C], 2019.
APA	Zhang, Q., Sun, JZ., & Mok, S. P. (2019). Low Dose SPECT Image Denoising Using a Generative Adversarial Network. 2019 International Conference on Medical Imaging with Deep Learning.

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