AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Radiation Dosage

Showing 481 to 490 of 501 articles

Clear Filters

Low-Dose Abdominal CT Using a Deep Learning-Based Denoising Algorithm: A Comparison with CT Reconstructed with Filtered Back Projection or Iterative Reconstruction Algorithm.

Korean journal of radiology
OBJECTIVE: To compare the image quality of low-dose (LD) computed tomography (CT) obtained using a deep learning-based denoising algorithm (DLA) with LD CT images reconstructed with a filtered back projection (FBP) and advanced modeled iterative reco...

[Quantitative Analysis of Emphysema in Ultra-high-resolution CT by Using Deep Learning Reconstruction: Comparison with Hybrid Iterative Reconstruction].

Nihon Hoshasen Gijutsu Gakkai zasshi
PURPOSE: The noise generated in ultra-high-resolution computed tomography (U-HRCT) images affects the quantitative analysis of emphysema. In this study, we compared the physical properties of reconstructed images for hybrid iterative reconstruction (...

[Application of Convolutional Neural Network for Evaluating CT Dose Using Image Noise Classification: A Phantom Study].

Nihon Hoshasen Gijutsu Gakkai zasshi
PURPOSE: It is well known that there is a trade-off relationship between image noise and exposure dose in X-ray computed tomography (CT) examination. Therefore, CT dose level was evaluated by using the CT image noise property. Although noise power sp...

[Development of CT Pelvimetry Using Deep Learning Based Reconstruction].

Nihon Hoshasen Gijutsu Gakkai zasshi
PURPOSE: X-ray pelvimetry is typically performed for the diagnosis of the cephalopelvic disproportion (CPD). The purpose of this study was to assess the utility of new computed tomography (CT) reconstruction "deep learning based reconstruction (DLR) ...

Deep Learning Reconstruction at CT: Phantom Study of the Image Characteristics.

Academic radiology
OBJECTIVES: Noise, commonly encountered on computed tomography (CT) images, can impact diagnostic accuracy. To reduce the image noise, we developed a deep-learning reconstruction (DLR) method that integrates deep convolutional neural networks into im...

Recent and Upcoming Technological Developments in Computed Tomography: High Speed, Low Dose, Deep Learning, Multienergy.

Investigative radiology
The advent of computed tomography (CT) has revolutionized radiology, and this revolution is still going on. Starting as a pure head scanner, modern CT systems are now able to perform whole-body examinations within a couple of seconds in isotropic res...

THE PROJECT OF ANOTHER LOW-COST METAPHASE FINDER (SECOND REPORT-APPLICATION OF ARTIFICIAL INTELLIGENCE).

Radiation protection dosimetry
Biological dosimetry is used to estimate individual absorbed radiation dose by quantifying an appropriate biological marker. The most popular gold-standard marker is the appearance of dicentric chromosomes in metaphase. The metaphase finder is a tool...

Investigation of Low-Dose CT Lung Cancer Screening Scan "Over-Range" Issue Using Machine Learning Methods.

Journal of digital imaging
Low-dose computed tomography (CT) lung cancer screening is recommended by the US Preventive Services Task Force for high lung cancer-risk populations. In this study, we investigated an important factor affecting the CT dose-the scan length, for this ...

Full-Dose PET Image Estimation from Low-Dose PET Image Using Deep Learning: a Pilot Study.

Journal of digital imaging
Positron emission tomography (PET) imaging is an effective tool used in determining disease stage and lesion malignancy; however, radiation exposure to patients and technicians during PET scans continues to draw concern. One way to minimize radiation...

Low-dose CT Denoising Using Edge Detection Layer and Perceptual Loss.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Low-dose CT imaging is a valid approach to reduce patients' exposure to X-ray radiation. However, reducing X-ray current increases noise and artifacts in the reconstructed CT images. Deep neural networks have been successfully employed to remove nois...