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Deep learning image reconstruction for CT: technical principles and clinical prospects
Filtered back projection (FBP) has been the standard CT image reconstruction method for 4
decades. A simple, fast, and reliable technique, FBP has delivered high-quality images in …
decades. A simple, fast, and reliable technique, FBP has delivered high-quality images in …
Application of artificial intelligence technology in oncology: Towards the establishment of precision medicine
Simple Summary Artificial intelligence (AI) technology has been advancing rapidly in recent
years and is being implemented in society. The medical field is no exception, and the clinical …
years and is being implemented in society. The medical field is no exception, and the clinical …
Image quality and dose reduction opportunity of deep learning image reconstruction algorithm for CT: a phantom study
Objectives To assess the impact on image quality and dose reduction of a new deep
learning image reconstruction (DLIR) algorithm compared with a hybrid iterative …
learning image reconstruction (DLIR) algorithm compared with a hybrid iterative …
Artificial intelligence in CT and MR imaging for oncological applications
Simple Summary The two most common cross-sectional imaging modalities, computed
tomography (CT) and magnetic resonance imaging (MRI), have shown enormous utility in …
tomography (CT) and magnetic resonance imaging (MRI), have shown enormous utility in …
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 …
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 …
Applications of artificial intelligence and deep learning in molecular imaging and radiotherapy
This brief review summarizes the major applications of artificial intelligence (AI), in particular
deep learning approaches, in molecular imaging and radiation therapy research. To this …
deep learning approaches, in molecular imaging and radiation therapy research. To this …
The augmented radiologist: artificial intelligence in the practice of radiology
In medicine, particularly in radiology, there are great expectations in artificial intelligence
(AI), which can “see” more than human radiologists in regard to, for example, tumor size …
(AI), which can “see” more than human radiologists in regard to, for example, tumor size …
Reduced-dose deep learning reconstruction for abdominal CT of liver metastases
Background Assessment of liver lesions is constrained as CT radiation doses are lowered;
evidence suggests deep learning reconstructions mitigate such effects. Purpose To evaluate …
evidence suggests deep learning reconstructions mitigate such effects. Purpose To evaluate …
Validation of deep-learning image reconstruction for coronary computed tomography angiography: impact on noise, image quality and diagnostic accuracy
Background Advances in image reconstruction are necessary to decrease radiation
exposure from coronary CT angiography (CCTA) further, but iterative reconstruction has …
exposure from coronary CT angiography (CCTA) further, but iterative reconstruction has …