AIMC Topic: Radiographic Image Interpretation, Computer-Assisted
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A Competition, Benchmark, Code, and Data for Using Artificial Intelligence to Detect Lesions in Digital Breast Tomosynthesis.
JAMA network open
Feb 1, 2023
IMPORTANCE: An accurate and robust artificial intelligence (AI) algorithm for detecting cancer in digital breast tomosynthesis (DBT) could significantly improve detection accuracy and reduce health care costs worldwide.
Deep Learning Image Reconstruction for CT: Technical Principles and Clinical Prospects.
Radiology
Jan 31, 2023
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 several clinical applications. However, with faster and more advanced ...
Deep Learning Denoising of Low-Dose Computed Tomography Chest Images: A Quantitative and Qualitative Image Analysis.
Journal of computer assisted tomography
Jan 28, 2023
PURPOSE: To assess deep learning denoised (DLD) computed tomography (CT) chest images at various low doses by both quantitative and qualitative perceptual image analysis.
Improving image quality with deep learning image reconstruction in double-low-dose head CT angiography compared with standard dose and adaptive statistical iterative reconstruction.
The British journal of radiology
Jan 18, 2023
OBJECTIVE: To demonstrate similar image quality with deep learning image reconstruction (DLIR) in reduced contrast medium (CM) and radiation dose (double-low-dose) head CT angiography (CTA), in comparison with standard-dose and adaptive statistical i...
"Image quality evaluation of the Precise image CT deep learning reconstruction algorithm compared to Filtered Back-projection and iDose: a phantom study at different dose levels".
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Jan 18, 2023
PURPOSE: To characterize the performance of the Precise Image (PI) deep learning reconstruction (DLR) algorithm for abdominal Computed Tomography (CT) imaging.
Development and Validation of a Deep Learning-Based Synthetic Bone-Suppressed Model for Pulmonary Nodule Detection in Chest Radiographs.
JAMA network open
Jan 3, 2023
IMPORTANCE: Dual-energy chest radiography exhibits better sensitivity than single-energy chest radiography, partly due to its ability to remove overlying anatomical structures.
Characteristics of the deep learning-based virtual monochromatic image with fast kilovolt-switching CT: a phantom study.
Radiological physics and technology
Dec 30, 2022
PURPOSE: We assessed the physical properties of virtual monochromatic images (VMIs) obtained with different energy levels in various contrast settings and radiation doses using deep learning-based spectral computed tomography (DL-Spectral CT) and com...
Evaluation of deep-learning image reconstruction for chest CT examinations at two different dose levels.
Journal of applied clinical medical physics
Dec 30, 2022
AIMS: The aims of the present study were to, for both a full-dose protocol and an ultra-low dose (ULD) protocol, compare the image quality of chest CT examinations reconstructed using TrueFidelity (Standard kernel) with corresponding examinations rec...
Comparison of image quality and pancreatic ductal adenocarcinoma conspicuity between the low-kVp and dual-energy CT reconstructed with deep-learning image reconstruction algorithm.
European journal of radiology
Dec 30, 2022
PURPOSE: To compare the image quality and conspicuity of pancreatic ductal adenocarcinoma (PDAC) between the low-kVp and dual-energy pancreatic protocol CT reconstructed with deep-learning image reconstruction (DLIR).
Low-contrast-dose liver CT using low monoenergetic images with deep learning-based denoising for assessing hepatocellular carcinoma: a randomized controlled noninferiority trial.
European radiology
Dec 28, 2022
OBJECTIVE: Low monoenergetic images obtained using noise-reduction techniques may reduce CT contrast media requirements. We aimed to investigate the effectiveness of low-contrast-dose CT using dual-energy CT and deep learning-based denoising (DLD) te...
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