Deep learning with convolutional neural network in radiology
Deep learning with a convolutional neural network (CNN) is gaining attention recently for its
high performance in image recognition. Images themselves can be utilized in a learning …
high performance in image recognition. Images themselves can be utilized in a learning …
State of the art in abdominal CT: the limits of iterative reconstruction algorithms
A Mileto, LS Guimaraes, CH McCollough, JG Fletcher… - Radiology, 2019 - pubs.rsna.org
The development and widespread adoption of iterative reconstruction (IR) algorithms for CT
have greatly facilitated the contemporary practice of radiation dose reduction during …
have greatly facilitated the contemporary practice of radiation dose reduction during …
Deep learning reconstruction improves image quality of abdominal ultra-high-resolution CT
M Akagi, Y Nakamura, T Higaki, K Narita, Y Honda… - European …, 2019 - Springer
Objectives Deep learning reconstruction (DLR) is a new reconstruction method; it introduces
deep convolutional neural networks into the reconstruction flow. This study was conducted …
deep convolutional neural networks into the reconstruction flow. This study was conducted …
Image quality assessment of abdominal CT by use of new deep learning image reconstruction: initial experience
OBJECTIVE. The purpose of this study was to perform quantitative and qualitative evaluation
of a deep learning image reconstruction (DLIR) algorithm in contrast-enhanced oncologic …
of a deep learning image reconstruction (DLIR) algorithm in contrast-enhanced oncologic …
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 …
Iterative low-dose CT reconstruction with priors trained by artificial neural network
Dose reduction in computed tomography (CT) is essential for decreasing radiation risk in
clinical applications. Iterative reconstruction algorithms are one of the most promising way to …
clinical applications. Iterative reconstruction algorithms are one of the most promising way to …
CT noise-reduction methods for lower-dose scanning: strengths and weaknesses of iterative reconstruction algorithms and new techniques
Iterative reconstruction (IR) algorithms are the most widely used CT noise-reduction method
to improve image quality and have greatly facilitated radiation dose reduction within the …
to improve image quality and have greatly facilitated radiation dose reduction within the …
Deep learning for low-dose CT denoising using perceptual loss and edge detection layer
M Gholizadeh-Ansari, J Alirezaie, P Babyn - Journal of digital imaging, 2020 - Springer
Low-dose CT denoising is a challenging task that has been studied by many researchers.
Some studies have used deep neural networks to improve the quality of low-dose CT …
Some studies have used deep neural networks to improve the quality of low-dose CT …
How I do it: managing radiation dose in CT
Computed tomography (CT) is an imaging test that is widely used worldwide to establish
medical diagnoses and perform image-guided interventions. More recently, concern has …
medical diagnoses and perform image-guided interventions. More recently, concern has …
[HTML][HTML] A review of deep learning CT reconstruction: concepts, limitations, and promise in clinical practice
TP Szczykutowicz, GV Toia, A Dhanantwari… - Current Radiology …, 2022 - Springer
Abstract Purpose of Review Deep Learning reconstruction (DLR) is the current state-of-the-
art method for CT image formation. Comparisons to existing filter back-projection, iterative …
art method for CT image formation. Comparisons to existing filter back-projection, iterative …