Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
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 …
A review of deep learning CT reconstruction: concepts, limitations, and promise in clinical practice
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 …
Deep learning reconstruction improves image quality of abdominal ultra-high-resolution CT
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
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 …
State of the art in abdominal CT: the limits of iterative reconstruction algorithms
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 …
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 …
Milestones in CT: past, present, and future
In 1971, the first patient CT examination by Ambrose and Hounsfield paved the way for not
only volumetric imaging of the brain but of the entire body. From the initial 5-minute scan for …
only volumetric imaging of the brain but of the entire body. From the initial 5-minute scan for …
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
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 …