A review on medical image denoising algorithms
SVM Sagheer, SN George - Biomedical signal processing and control, 2020 - Elsevier
Over the past two decades, medical imaging and diagnostic techniques have gained
immense attraction due to the rapid development in computing, internet, data storage and …
immense attraction due to the rapid development in computing, internet, data storage and …
Artificial intelligence in diagnostic imaging: impact on the radiography profession
The arrival of artificially intelligent systems into the domain of medical imaging has focused
attention and sparked much debate on the role and responsibilities of the radiologist …
attention and sparked much debate on the role and responsibilities of the radiologist …
Image quality and lesion detection on deep learning reconstruction and iterative reconstruction of submillisievert chest and abdominal CT
R Singh, SR Digumarthy, VV Muse… - American Journal of …, 2020 - Am Roentgen Ray Soc
OBJECTIVE. The objective of this study was to compare image quality and clinically
significant lesion detection on deep learning reconstruction (DLR) and iterative …
significant lesion detection on deep learning reconstruction (DLR) and iterative …
The use of deep learning methods in low-dose computed tomography image reconstruction: a systematic review
Conventional reconstruction techniques, such as filtered back projection (FBP) and iterative
reconstruction (IR), which have been utilised widely in the image reconstruction process of …
reconstruction (IR), which have been utilised widely in the image reconstruction process of …
Benchmarking deep learning‐based low‐dose CT image denoising algorithms
Background Long‐lasting efforts have been made to reduce radiation dose and thus the
potential radiation risk to the patient for computed tomography (CT) acquisitions without …
potential radiation risk to the patient for computed tomography (CT) acquisitions without …
One sample diffusion model in projection domain for low-dose CT imaging
Low-dose computed tomography (CT) plays a significant role in reducing the radiation risk in
clinical applications. However, lowering the radiation dose will significantly degrade the …
clinical applications. However, lowering the radiation dose will significantly degrade the …
Iterative tomographic reconstruction with TV prior for low-dose CBCT dental imaging
Objective. Cone-beam computed tomography is becoming more and more popular in
applications such as 3D dental imaging. Iterative methods compared to the standard …
applications such as 3D dental imaging. Iterative methods compared to the standard …
An efficient sinogram domain fully convolutional interpolation network for sparse-view computed tomography reconstruction
Recently, deep learning techniques have been used for low-dose CT (LDCT) reconstruction
to reduce the radiation risk for patients. Despite the improvement in performance, the …
to reduce the radiation risk for patients. Despite the improvement in performance, the …
One-Sample Diffusion Modeling in Projection Domain for Low-Dose CT Imaging
B Huang, S Lu, L Zhang, B Lin, W Wu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Low-dose computed tomography (CT) is crucial in clinical applications for reducing radiation
risks. However, lowering the radiation dose will significantly degrade the image quality. In …
risks. However, lowering the radiation dose will significantly degrade the image quality. In …
Convergent–diffusion denoising model for multi-scenario CT image reconstruction
A generic and versatile CT Image Reconstruction (CTIR) scheme can efficiently mitigate
imaging noise resulting from inherent physical limitations, substantially bolstering the …
imaging noise resulting from inherent physical limitations, substantially bolstering the …