AIMC Topic: Radiographic Image Interpretation, Computer-Assisted
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The effect of deep learning reconstruction on abdominal CT densitometry and image quality: a systematic review and meta-analysis.
European radiology
Dec 15, 2021
OBJECTIVE: To determine the difference in CT values and image quality of abdominal CT images reconstructed by filtered back-projection (FBP), hybrid iterative reconstruction (IR), and deep learning reconstruction (DLR).
Noise reduction profile: A new method for evaluation of noise reduction techniques in CT.
Medical physics
Dec 15, 2021
PURPOSE: Noise power spectrum (NPS) is a commonly used performance metric to evaluate noise-reduction techniques (NRT) in imaging systems. The images reconstructed with and without an NRT can be compared via their NPS to better understand the NRT's e...
Stand-Alone Use of Artificial Intelligence for Digital Mammography and Digital Breast Tomosynthesis Screening: A Retrospective Evaluation.
Radiology
Dec 14, 2021
Background Use of artificial intelligence (AI) as a stand-alone reader for digital mammography (DM) or digital breast tomosynthesis (DBT) breast screening could ease radiologists' workload while maintaining quality. Purpose To retrospectively evaluat...
Independent evaluation of 12 artificial intelligence solutions for the detection of tuberculosis.
Scientific reports
Dec 13, 2021
There have been few independent evaluations of computer-aided detection (CAD) software for tuberculosis (TB) screening, despite the rapidly expanding array of available CAD solutions. We developed a test library of chest X-ray (CXR) images which was ...
X-Ray Film under Artificial Intelligence Algorithm in the Evaluation for Nursing Effect of Gamma Nail Internal Fixation in Elderly Patients with Intertrochanteric Fracture of Femur.
Computational and mathematical methods in medicine
Nov 30, 2021
The aim of this work was to explore the effects of Gamma nail internal fixation for intertrochanteric fracture of femur by X-ray film classification and recognition method based on artificial intelligence algorithm. The study subjects were 100 elderl...
Image quality in liver CT: low-dose deep learning vs standard-dose model-based iterative reconstructions.
European radiology
Nov 25, 2021
OBJECTIVES: To compare the overall image quality and detectability of significant (malignant and pre-malignant) liver lesions of low-dose liver CT (LDCT, 33.3% dose) using deep learning denoising (DLD) to standard-dose CT (SDCT, 100% dose) using mode...
Complex Relationship Between Artificial Intelligence and CT Radiation Dose.
Academic radiology
Nov 24, 2021
Concerns over need for CT radiation dose optimization and reduction led to improved scanner efficiency and introduction of several reconstruction techniques and image processing-based software. The latest technologies use artificial intelligence (AI)...
Performance of a deep learning-based lung nodule detection system as an alternative reader in a Chinese lung cancer screening program.
European journal of radiology
Nov 24, 2021
OBJECTIVE: To evaluate the performance of a deep learning-based computer-aided detection (DL-CAD) system in a Chinese low-dose CT (LDCT) lung cancer screening program.
A deep-learning reconstruction algorithm that improves the image quality of low-tube-voltage coronary CT angiography.
European journal of radiology
Nov 24, 2021
PURPOSE: To assess the image quality (IQ) of low tube voltage coronary CT angiography (CCTA) images reconstructed with deep learning image reconstruction (DLIR).
Assessment of gastric wall structure using ultra-high-resolution computed tomography.
European journal of radiology
Nov 24, 2021
PURPOSE: To evaluate the image quality of ultra-high-resolution CT (U-HRCT) in the comparison among four different reconstruction methods, focusing on the gastric wall structure, and to compare the conspicuity of a three-layered structure of the gast...
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