Inter-slice consistency for unpaired low-dose CT denoising using boosted contrastive learning
The research field of low-dose computed tomography (LDCT) denoising is primarily
dominated by supervised learning-based approaches, which necessitate the accurate …
dominated by supervised learning-based approaches, which necessitate the accurate …
Low-dose CT denoising via sinogram inner-structure transformer
Low-Dose Computed Tomography (LDCT) technique, which reduces the radiation harm to
human bodies, is now attracting increasing interest in the medical imaging field. As the …
human bodies, is now attracting increasing interest in the medical imaging field. As the …
Performance of a deep learning‐based CT image denoising method: Generalizability over dose, reconstruction kernel, and slice thickness
Purpose Deep learning (DL) is rapidly finding applications in low‐dose CT image denoising.
While having the potential to improve the image quality (IQ) over the filtered back projection …
While having the potential to improve the image quality (IQ) over the filtered back projection …
Self‐supervised denoising of projection data for low‐dose cone‐beam CT
K Choi, SH Kim, S Kim - Medical Physics, 2023 - Wiley Online Library
Abstract Background Convolutional neural networks (CNNs) have shown promising results
in image denoising tasks. While most existing CNN‐based methods depend on supervised …
in image denoising tasks. While most existing CNN‐based methods depend on supervised …
Adapting low‐dose CT denoisers for texture preservation using zero‐shot local noise‐level matching
Background On enhancing the image quality of low‐dose computed tomography (LDCT),
various denoising methods have achieved meaningful improvements. However, they …
various denoising methods have achieved meaningful improvements. However, they …
A deeper convolutional neural network for denoising low-dose CT images
In recent years, CNN has been gaining attention as a powerful denoising tool after the
pioneering work [7], developing 3-layer convolutional neural network (CNN). However, the 3 …
pioneering work [7], developing 3-layer convolutional neural network (CNN). However, the 3 …
Simulating arbitrary dose levels and independent noise image pairs from a single CT scan
S Wang, AS Wang - … Conference on Image Formation in X-Ray …, 2022 - spiedigitallibrary.org
Deep learning-based image denoising and reconstruction methods have shown promising
results for low-dose CT. When high-quality reference images are not available for training …
results for low-dose CT. When high-quality reference images are not available for training …
Investigation of low-dose CT image denoising using unpaired deep learning methods
Low-dose computed tomography (LDCT) is desired due to prevalence and ionizing radiation
of CT, but suffers elevated noise. To improve LDCT image quality, an image-domain …
of CT, but suffers elevated noise. To improve LDCT image quality, an image-domain …
Noise Conditioned Weight Modulation for Robust and Generalizable Low Dose CT Denoising
S Bera, PK Biswas - … Conference on Medical Image Computing and …, 2023 - Springer
Deep neural networks have been extensively studied for denoising low-dose computed
tomography (LDCT) images, but some challenges related to robustness and generalization …
tomography (LDCT) images, but some challenges related to robustness and generalization …
3d residual convolutional neural network for low dose ct denoising
AA Zamyatin, L Yu, D Rozas - Medical Imaging 2022: Physics …, 2022 - spiedigitallibrary.org
CT continues to be one of the most widely used medical imaging modalities. Concerns
about long term effect of x-ray radiation on patients have led to efforts to reduce the x-ray …
about long term effect of x-ray radiation on patients have led to efforts to reduce the x-ray …