AIMC Topic: Radiographic Image Interpretation, Computer-Assisted

Clear Filters Showing 31 to 40 of 1289 articles

Deep Learning-enhanced Opportunistic Osteoporosis Screening in Ultralow-Voltage (80 kV) Chest CT: A Preliminary Study.

Academic radiology May 2, 2025
RATIONALE AND OBJECTIVES: To explore the feasibility of deep learning (DL)-enhanced, fully automated bone mineral density (BMD) measurement using the ultralow-voltage 80 kV chest CT scans performed for lung cancer screening.
Radiographic Image Interpretation, Computer-Assisted Feasibility Studies Osteoporosis Radiography, Thoracic Tomography, X-Ray Computed Female Aged Aged, 80 and over Male Middle Aged Deep Learning Lung Neoplasms Humans Bone Density Retrospective Studies
View on PubMed DOI

A deep learning algorithm for automated adrenal gland segmentation on non-contrast CT images.

BMC medical imaging May 1, 2025
BACKGROUND: The adrenal glands are small retroperitoneal organs, few reference standards exist for adrenal CT measurements in clinical practice. This study aims to develop a deep learning (DL) model for automated adrenal gland segmentation on non-con...
Middle Aged Deep Learning Adolescent Radiographic Image Interpretation, Computer-Assisted Observer Variation Aged, 80 and over Young Adult Humans Adult Algorithms Male Tomography, X-Ray Computed Adrenal Glands Female Aged
View on PubMed DOI

Impact of Photon-counting Detector Computed Tomography on a Quantitative Interstitial Lung Disease Machine Learning Model.

Journal of thoracic imaging May 1, 2025
PURPOSE: Compare the impact of photon-counting detector computed tomography (PCD-CT) to conventional CT on an interstitial lung disease (ILD) quantitative machine learning (QML) model.
Photons Middle Aged Lung Radiographic Image Interpretation, Computer-Assisted Lung Diseases, Interstitial Tomography, X-Ray Computed Female Aged Adult Humans Male Machine Learning Retrospective Studies
View on PubMed DOI

Detection of Pulmonary Nodules on Ultra-low Dose Chest Computed Tomography With Deep-learning Image Reconstruction Algorithm.

Journal of thoracic imaging May 1, 2025
PURPOSE: To evaluate the accuracy of ultra-low dose (ULD) chest computed tomography (CT), with a radiation exposure equivalent to a 2-view chest x-ray, for pulmonary nodule detection using deep learning image reconstruction (DLIR).
Female Aged Aged, 80 and over Adult Sensitivity and Specificity Cross-Sectional Studies Male Middle Aged Lung Humans Algorithms Prospective Studies Tomography, X-Ray Computed Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Radiography, Thoracic Deep Learning Lung Neoplasms Multiple Pulmonary Nodules Solitary Pulmonary Nodule
View on PubMed DOI

Tumor grade-titude: XGBoost radiomics paves the way for RCC classification.

European journal of radiology Apr 29, 2025
This study aimed to develop and evaluate a non-invasive XGBoost-based machine learning model using radiomic features extracted from pre-treatment CT images to differentiate grade 4 renal cell carcinoma (RCC) from lower-grade tumours. A total of 102 R...
Humans Machine Learning Tomography, X-Ray Computed Adult Sensitivity and Specificity Radiomics Male Middle Aged Female Reproducibility of Results Aged Aged, 80 and over Carcinoma, Renal Cell Contrast Media Boosting Machine Learning Algorithms Neoplasm Grading Radiographic Image Interpretation, Computer-Assisted Kidney Neoplasms
View on PubMed DOI

Application of deep learning reconstruction combined with time-resolved post-processing method to improve image quality in CTA derived from low-dose cerebral CT perfusion data.

BMC medical imaging Apr 29, 2025
BACKGROUND: To assess the effect of the combination of deep learning reconstruction (DLR) and time-resolved maximum intensity projection (tMIP) or time-resolved average (tAve) post-processing method on image quality of CTA derived from low-dose cereb...
Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Adult Humans Signal-To-Noise Ratio Retrospective Studies Computed Tomography Angiography Male Female Middle Aged Aged Deep Learning Image Processing, Computer-Assisted
View on PubMed DOI

Application and optimization of the U-Net++ model for cerebral artery segmentation based on computed tomographic angiography images.

European journal of radiology Apr 27, 2025
Accurate segmentation of cerebral arteries on computed tomography angiography (CTA) images is essential for the diagnosis and management of cerebrovascular diseases, including ischemic stroke. This study implemented a deep learning-based U-Net++ mode...
Radiographic Image Interpretation, Computer-Assisted Cerebrovascular Disorders Computed Tomography Angiography Cerebral Angiography Cerebral Arteries Humans Reproducibility of Results Deep Learning
View on PubMed DOI

Reduction of radiation exposure in chest radiography using deep learning-based noise reduction processing: A phantom and retrospective clinical study.

Radiography (London, England : 1995) Apr 24, 2025
INTRODUCTION: Intelligent noise reduction (INR), a deep learning-based noise reduction developed by Canon, is used in planar radiography to improve image quality and reduce patient exposure dose. This study aimed to evaluate the reduction of patient ...
Radiation Exposure Female Humans Aged Retrospective Studies Deep Learning Adult Radiographic Image Interpretation, Computer-Assisted Male Radiation Dosage Middle Aged Radiography, Thoracic Phantoms, Imaging
View on PubMed DOI

Evaluating artificial intelligence performance in medical image analysis: Sensitivity, specificity, accuracy, and precision of ChatGPT-4o on Kellgren-Lawrence grading of knee X-ray radiographs.

The Knee Apr 23, 2025
BACKGROUND: Recent advancements in artificial intelligence, including ChatGPT, have enabled its application in medical image analysis.This study aimed to evaluate the sensitivity and specificity of ChatGPT in assessing knee osteoarthritis (KOA) radio...
Artificial Intelligence Retrospective Studies Generative Artificial Intelligence Female Humans Adult Radiography Reproducibility of Results Sensitivity and Specificity Radiographic Image Interpretation, Computer-Assisted Aged Male Knee Joint Middle Aged Osteoarthritis, Knee ROC Curve
View on PubMed DOI

Impact of CT reconstruction algorithms on pericoronary and epicardial adipose tissue attenuation.

European journal of radiology Apr 23, 2025
OBJECTIVE: This study aims to investigate the impact of adaptive statistical iterative reconstruction-Veo (ASIR-V) and deep learning image reconstruction (DLIR) algorithms on the quantification of pericoronary adipose tissue (PCAT) and epicardial adi...
Pericardium Epicardial Adipose Tissue Adipose Tissue Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Computed Tomography Angiography Humans Algorithms Retrospective Studies Tomography, X-Ray Computed Female Aged Male Middle Aged Deep Learning
View on PubMed DOI
Popular Topics
Recent Journals