AIMC Topic: Radiographic Image Interpretation, Computer-Assisted

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Deep Learning Reconstruction Shows Better Lung Nodule Detection for Ultra-Low-Dose Chest CT.

Radiology Jan 18, 2022
Background Ultra-low-dose (ULD) CT could facilitate the clinical implementation of large-scale lung cancer screening while minimizing the radiation dose. However, traditional image reconstruction methods are associated with image noise in low-dose ac...
Humans Algorithms Prospective Studies Tomography, X-Ray Computed Female Precancerous Conditions Lung Neoplasms Radiation Dosage Early Detection of Cancer Radiographic Image Interpretation, Computer-Assisted Male Lung Deep Learning
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Reduced-Dose Deep Learning Reconstruction for Abdominal CT of Liver Metastases.

Radiology Jan 11, 2022
Background Assessment of liver lesions is constrained as CT radiation doses are lowered; evidence suggests deep learning reconstructions mitigate such effects. Purpose To evaluate liver metastases and image quality between reduced-dose deep learning ...
Algorithms Prospective Studies Tomography, X-Ray Computed Humans Liver Neoplasms Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Female Male Deep Learning
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Cloud-Based Lung Tumor Detection and Stage Classification Using Deep Learning Techniques.

BioMed research international Jan 10, 2022
Artificial intelligence (AI), Internet of Things (IoT), and the cloud computing have recently become widely used in the healthcare sector, which aid in better decision-making for a radiologist. PET imaging or positron emission tomography is one of th...
Cloud Computing Humans Positron Emission Tomography Computed Tomography Databases, Factual Neoplasm Staging Deep Learning Radiographic Image Interpretation, Computer-Assisted Lung Neoplasms
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Clinical impact of a deep learning system for automated detection of missed pulmonary nodules on routine body computed tomography including the chest region.

European radiology Jan 9, 2022
OBJECTIVES: To evaluate the clinical impact of a deep learning system (DLS) for automated detection of pulmonary nodules on computed tomography (CT) images as a second reader.
Lung Neoplasms Multiple Pulmonary Nodules Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Sensitivity and Specificity Humans Deep Learning Retrospective Studies
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Clinical acceptance of deep learning reconstruction for abdominal CT imaging: objective and subjective image quality and low-contrast detectability assessment.

European radiology Jan 6, 2022
OBJECTIVE: To evaluate the image quality and clinical acceptance of a deep learning reconstruction (DLR) algorithm compared to traditional iterative reconstruction (IR) algorithms.
Radiation Dosage Phantoms, Imaging Tomography, X-Ray Computed Deep Learning Radiographic Image Interpretation, Computer-Assisted Humans Algorithms
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Deep learning versus iterative image reconstruction algorithm for head CT in trauma.

Emergency radiology Jan 5, 2022
PURPOSE: To compare the image quality between a deep learning-based image reconstruction algorithm (DLIR) and an adaptive statistical iterative reconstruction algorithm (ASiR-V) in noncontrast trauma head CT.
Humans Image Processing, Computer-Assisted Radiographic Image Interpretation, Computer-Assisted Algorithms Radiation Dosage Tomography, X-Ray Computed Deep Learning
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Deep Learning-Assisted Diagnosis of Pediatric Skull Fractures on Plain Radiographs.

Korean journal of radiology Jan 4, 2022
OBJECTIVE: To develop and evaluate a deep learning-based artificial intelligence (AI) model for detecting skull fractures on plain radiographs in children.
Skull Radiography Radiographic Image Interpretation, Computer-Assisted Deep Learning Skull Fractures Humans Child Artificial Intelligence Retrospective Studies Sensitivity and Specificity
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Application of Deep Learning in Lung Cancer Imaging Diagnosis.

Journal of healthcare engineering Jan 3, 2022
Lung cancer is one of the malignant tumors with the highest fatality rate and nearest to our lives. It poses a great threat to human health and it mainly occurs in smokers. In our country, with the acceleration of industrialization, environmental pol...
Radiographic Image Interpretation, Computer-Assisted Humans Lung Deep Learning Lung Neoplasms Solitary Pulmonary Nodule
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Improving Radiographic Fracture Recognition Performance and Efficiency Using Artificial Intelligence.

Radiology Dec 21, 2021
Background Missed fractures are a common cause of diagnostic discrepancy between initial radiographic interpretation and the final read by board-certified radiologists. Purpose To assess the effect of assistance by artificial intelligence (AI) on dia...
Datasets as Topic Diagnostic Errors Retrospective Studies Humans Male Female Artificial Intelligence Middle Aged Sensitivity and Specificity Fractures, Bone Radiographic Image Interpretation, Computer-Assisted Quality Improvement
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Image quality and radiologists' subjective acceptance using model-based iterative and deep learning reconstructions as adjuncts to ultrahigh-resolution CT in low-dose contrast-enhanced abdominopelvic CT: phantom and clinical pilot studies.

Abdominal radiology (New York) Dec 16, 2021
PURPOSE: In contrast-enhanced abdominopelvic CT (CE-APCT) for oncologic follow-up, ultrahigh-resolution CT (UHRCT) may improve depiction of fine lesions and low-dose scans are desirable for minimizing the potential adverse effects by ionizing radiati...
Algorithms Tomography, X-Ray Computed Deep Learning Humans Radiation Dosage Pilot Projects Radiologists Radiographic Image Interpretation, Computer-Assisted
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