Feb 3, 2021 · We present a new self-supervised method for CT denoising. Unlike existing self-supervised approaches, the proposed method requires only noisy CT projections.
The reduction of the radiation dose decreases the risks to the patients but raises the noise level, affecting the quality of the images and their ul- timate ...
Feb 3, 2021 · This paper presents a new self-supervised method for CT denoising that requires only noisy CT projections and exploits the connections ...
Feb 3, 2021 · In this paper, we present a new self-supervised method for CT denoising. Unlike existing self-supervised approaches, the proposed method ...
In this paper, we present a new self-supervised method for CT denoising. Unlike existing self-supervised approaches, the proposed method requires only noisy CT ...
PURPOSE In this paper, we propose a novel self-supervised learning method that reduces noise in projections acquired by ordinary CBCT scans.
In this paper, we present a new self-supervised method for CT denoising. Unlike existing self-supervised approaches, the proposed method requires only noisy CT ...
Low-dose CT image denoising without high-dose reference images
ui.adsabs.harvard.edu › abs › abstract
In this work, we applied the N2N training to low-dose CT denoising. Our results show that the N2N training works in both count and image domains without using ...
Missing: Projections. | Show results with:Projections.
Apr 20, 2023 · In this paper, we propose a novel self-supervised learning method that reduces noise in projections acquired by ordinary CBCT scans.
In this paper, we propose a novel LDCT image denoising method based on transformer combined with convolutional neural network (CNN).