AIMC Topic: Radiation Dosage

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A deep learning method for the recovery of standard-dose imaging quality from ultra-low-dose PET on wavelet domain.

European journal of nuclear medicine and molecular imaging Nov 25, 2024
PURPOSE: Recent development in positron emission tomography (PET) dramatically increased the effective sensitivity by increasing the geometric coverage leading to total-body PET imaging. This encouraging breakthrough brings the hope of ultra-low dose...
Positron-Emission Tomography Humans Radiation Dosage Deep Learning Wavelet Analysis Image Processing, Computer-Assisted
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The Pivotal Role of Baseline LDCT for Lung Cancer Screening in the Era of Artificial Intelligence.

Archivos de bronconeumologia Nov 22, 2024
In this narrative review, we address the ongoing challenges of lung cancer (LC) screening using chest low-dose computerized tomography (LDCT) and explore the contributions of artificial intelligence (AI), in overcoming them. We focus on evaluating th...
Artificial Intelligence Tomography, X-Ray Computed Pulmonary Disease, Chronic Obstructive Deep Learning Humans Lung Neoplasms Early Detection of Cancer Radiation Dosage
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An AI deep learning algorithm for detecting pulmonary nodules on ultra-low-dose CT in an emergency setting: a reader study.

European radiology experimental Nov 20, 2024
BACKGROUND: To retrospectively assess the added value of an artificial intelligence (AI) algorithm for detecting pulmonary nodules on ultra-low-dose computed tomography (ULDCT) performed at the emergency department (ED).
Lung Neoplasms Multiple Pulmonary Nodules Solitary Pulmonary Nodule Artificial Intelligence Retrospective Studies Emergency Service, Hospital Humans Male Algorithms Prospective Studies Middle Aged Deep Learning Tomography, X-Ray Computed Female Aged Radiation Dosage
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Deep learning based ultra-low dose fan-beam computed tomography image enhancement algorithm: Feasibility study in image quality for radiotherapy.

Journal of applied clinical medical physics Nov 14, 2024
OBJECTIVE: We investigated the feasibility of deep learning-based ultra-low dose kV-fan-beam computed tomography (kV-FBCT) image enhancement algorithm for clinical application in abdominal and pelvic tumor radiotherapy.
Humans Algorithms Prospective Studies Radiotherapy, Image-Guided Tomography, X-Ray Computed Radiotherapy Planning, Computer-Assisted Radiographic Image Enhancement Radiation Dosage Signal-To-Noise Ratio Pelvic Neoplasms Image Processing, Computer-Assisted Radiotherapy Dosage Female Male Radiographic Image Interpretation, Computer-Assisted Radiotherapy, Intensity-Modulated Deep Learning Phantoms, Imaging Abdominal Neoplasms Feasibility Studies Organs at Risk
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Feasibility of Ultra-low Radiation and Contrast Medium Dosage in Aortic CTA Using Deep Learning Reconstruction at 60 kVp: An Image Quality Assessment.

Academic radiology Nov 13, 2024
OBJECTIVE: To assess the viability of using ultra-low radiation and contrast medium (CM) dosage in aortic computed tomography angiography (CTA) through the application of low tube voltage (60kVp) and a novel deep learning image reconstruction algorit...
Phantoms, Imaging Prospective Studies Computed Tomography Angiography Female Humans Aged Aortography Male Algorithms Radiographic Image Interpretation, Computer-Assisted Feasibility Studies Radiation Dosage Middle Aged Aorta Deep Learning Contrast Media
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Deep learning prediction of scenario doses for direct plan robustness evaluations in IMPT for head-and-neck.

Physics in medicine and biology Nov 12, 2024
. Intensity modulated proton therapy (IMPT) is susceptible to uncertainties in patient setup and proton range. Robust optimization is employed in IMPT treatment planning to ensure sufficient coverage of the clinical target volume (CTV) in predefined ...
Radiation Dosage Radiotherapy Dosage Radiotherapy, Intensity-Modulated Proton Therapy Tomography, X-Ray Computed Deep Learning Head and Neck Neoplasms Radiotherapy Planning, Computer-Assisted Humans
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Evaluating the Efficacy of Deep Learning Reconstruction in Reducing Radiation Dose for Computer-Aided Volumetry for Liver Tumor: A Phantom Study.

Journal of computer assisted tomography Nov 5, 2024
OBJECTIVE: The purpose of this study was to compare radiation dose reduction capability for accurate liver tumor measurements of a computer-aided volumetry (CAD v ) software for filtered back projection (FBP), hybrid-type iterative reconstruction (IR...
Radiation Dosage Signal-To-Noise Ratio Phantoms, Imaging Liver Neoplasms Liver Radiographic Image Interpretation, Computer-Assisted Humans Tomography, X-Ray Computed Deep Learning
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Significance of Image Reconstruction Parameters for Future Lung Cancer Risk Prediction Using Low-Dose Chest Computed Tomography and the Open-Access Sybil Algorithm.

Investigative radiology Oct 23, 2024
PURPOSE: Sybil is a validated publicly available deep learning-based algorithm that can accurately predict lung cancer risk from a single low-dose computed tomography (LDCT) scan. We aimed to study the effect of image reconstruction parameters and CT...
Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Female Humans Middle Aged Aged Risk Assessment Algorithms Male Deep Learning Tomography, X-Ray Computed Lung Neoplasms
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Lung nodule classification using radiomics model trained on degraded SDCT images.

Computer methods and programs in biomedicine Oct 23, 2024
BACKGROUND AND OBJECTIVE: Low-dose computed tomography (LDCT) screening has shown promise in reducing lung cancer mortality; however, it suffers from high false positive rates and a scarcity of available annotated datasets. To overcome these challeng...
Humans Reproducibility of Results Radiomics Image Processing, Computer-Assisted Lung Neoplasms Machine Learning Algorithms Tomography, X-Ray Computed Radiation Dosage Logistic Models Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted
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Deep Learning-Based Estimation of Radiographic Position to Automatically Set Up the X-Ray Prime Factors.

Journal of imaging informatics in medicine Oct 14, 2024
Radiation dose and image quality in radiology are influenced by the X-ray prime factors: KVp, mAs, and source-detector distance. These parameters are set by the X-ray technician prior to the acquisition considering the radiographic position. A wrong ...
Deep Learning Radiography Radiation Dosage X-Rays Humans
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