AIMC Topic: Radiographic Image Interpretation, Computer-Assisted
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Editorial Comment: Doing More With Less-Deep Learning Iterative Reconstruction Can Improve Diagnostic Image Quality in Pediatric Low-Dose Body CT.
AJR. American journal of roentgenology
Mar 9, 2022
Radiation and iodine dose reduced thoraco-abdomino-pelvic dual-energy CT at 40 keV reconstructed with deep learning image reconstruction.
The British journal of radiology
Mar 4, 2022
OBJECTIVE: To evaluate the feasibility of a simultaneous reduction of radiation and iodine doses in dual-energy thoraco-abdomino-pelvic CT reconstructed with deep learning image reconstruction (DLIR).
Deep learning improves image quality and radiomics reproducibility for high-speed four-dimensional computed tomography reconstruction.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Mar 4, 2022
BACKGROUND AND PURPOSE: Hybrid iterative reconstruction (HIR) is the most commonly used algorithm for four-dimensional computed tomography (4DCT) reconstruction due to its high speed. However, the image quality is worse than that of model-based itera...
Deep learning image reconstruction for improving image quality of contrast-enhanced dual-energy CT in abdomen.
European radiology
Mar 3, 2022
OBJECTIVES: To evaluate the usefulness of deep learning image reconstruction (DLIR) to improve the image quality of dual-energy computed tomography (DECT) of the abdomen, compared to hybrid iterative reconstruction (IR).
Radiation Dose Reduction for 80-kVp Pediatric CT Using Deep Learning-Based Reconstruction: A Clinical and Phantom Study.
AJR. American journal of roentgenology
Feb 23, 2022
Deep learning-based reconstruction (DLR) may facilitate CT radiation dose reduction, but a paucity of literature has compared lower-dose DLR images with standard-dose iterative reconstruction (IR) images or explored application of DLR to low-tube-vo...
Deep learning reconstruction improves radiomics feature stability and discriminative power in abdominal CT imaging: a phantom study.
European radiology
Feb 16, 2022
OBJECTIVES: To compare image quality of deep learning reconstruction (AiCE) for radiomics feature extraction with filtered back projection (FBP), hybrid iterative reconstruction (AIDR 3D), and model-based iterative reconstruction (FIRST).
Image quality assessment of artificial intelligence iterative reconstruction for low dose aortic CTA: A feasibility study of 70 kVp and reduced contrast medium volume.
European journal of radiology
Feb 15, 2022
PURPOSE: To investigate the image quality and feasibility of a novel artificial intelligence iterative reconstruction (AIIR) algorithm for aortic computer tomography angiography (CTA) with a low radiation dose and contrast material (CM) dosage protoc...
Compound W-Net with Fully Accumulative Residual Connections for Liver Segmentation Using CT Images.
Computational and mathematical methods in medicine
Feb 9, 2022
Computed tomography (CT) is a common modality for liver diagnosis, treatment, and follow-up process. Providing accurate liver segmentation using CT images is a crucial step towards those tasks. In this paper, we propose a stacked 2-U-Nets model with ...
Impact of noise reduction on radiation dose reduction potential of virtual monochromatic spectral images: Comparison of phantom images with conventional 120 kVp images using deep learning image reconstruction and hybrid iterative reconstruction.
European journal of radiology
Feb 5, 2022
PURPOSE: To assess the effects of deep learning image reconstruction (DLIR) and hybrid iterative reconstruction (HIR) on the image quality of virtual monochromatic spectral (VMS) images and to investigate the dose reduction potential of the VMS and c...
Deep learning based diagnosis for cysts and tumors of jaw with massive healthy samples.
Scientific reports
Feb 3, 2022
We aimed to develop an explainable and reliable method to diagnose cysts and tumors of the jaw with massive panoramic radiographs of healthy peoples based on deep learning, since collecting and labeling massive lesion samples are time-consuming, and ...
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