AIMC Topic: Tomography, X-Ray Computed

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AI implementation: Radiologists' perspectives on AI-enabled opportunistic CT screening.

Clinical imaging Sep 10, 2024
OBJECTIVE: AI adoption requires perceived value by end-users. AI-enabled opportunistic CT screening (OS) detects incidental clinically meaningful imaging risk markers on CT for potential preventative health benefit. This investigation assesses radiol...
Mass Screening Humans Radiologists Middle Aged Surveys and Questionnaires Artificial Intelligence Attitude of Health Personnel Tomography, X-Ray Computed Female Male
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Developing an ensemble machine learning study: Insights from a multi-center proof-of-concept study.

PloS one Sep 10, 2024
BACKGROUND: To address the numerous unmeet clinical needs, in recent years several Machine Learning models applied to medical images and clinical data have been introduced and developed. Even when they achieve encouraging results, they lack evolution...
Lung Neoplasms Proof of Concept Study Tomography, X-Ray Computed Humans Female Machine Learning Male Algorithms
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PelviNet: A Collaborative Multi-agent Convolutional Network for Enhanced Pelvic Image Registration.

Journal of imaging informatics in medicine Sep 9, 2024
PelviNet introduces a groundbreaking multi-agent convolutional network architecture tailored for enhancing pelvic image registration. This innovative framework leverages shared convolutional layers, enabling synchronized learning among agents and ens...
Neural Networks, Computer Tomography, X-Ray Computed Humans Imaging, Three-Dimensional Image Processing, Computer-Assisted Pelvis
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Artificial intelligence system for identification of overlooked lung metastasis in abdominopelvic computed tomography scans of patients with malignancy.

Diagnostic and interventional radiology (Ankara, Turkey) Sep 9, 2024
PURPOSE: This study aimed to evaluate whether an artificial intelligence (AI) system can identify basal lung metastatic nodules examined using abdominopelvic computed tomography (CT) that were initially overlooked by radiologists.
Middle Aged Lung ROC Curve Pelvis Radiography, Abdominal Lung Neoplasms Abdomen Adult Sensitivity and Specificity Male Retrospective Studies Female Tomography, X-Ray Computed Aged Humans Aged, 80 and over Artificial Intelligence
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Precise ablation zone segmentation on CT images after liver cancer ablation using semi-automatic CNN-based segmentation.

Medical physics Sep 9, 2024
BACKGROUND: Ablation zone segmentation in contrast-enhanced computed tomography (CECT) images enables the quantitative assessment of treatment success in the ablation of liver lesions. However, fully automatic liver ablation zone segmentation in CT i...
Automation Tomography, X-Ray Computed Humans Ablation Techniques Liver Neoplasms Neural Networks, Computer Image Processing, Computer-Assisted
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Artificial intelligence-based quantification of pulmonary HRCT (AIqpHRCT) for the evaluation of interstitial lung disease in patients with inflammatory rheumatic diseases.

Rheumatology international Sep 9, 2024
High-resolution computed tomography (HRCT) is important for diagnosing interstitial lung disease (ILD) in inflammatory rheumatic disease (IRD) patients. However, visual ILD assessment via HRCT often has high inter-reader variability. Artificial intel...
Humans Artificial Intelligence Lung Aged Male Tomography, X-Ray Computed Lung Diseases, Interstitial Adult Middle Aged Rheumatic Diseases Female Reproducibility of Results
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Accelerating segmentation of fossil CT scans through Deep Learning.

Scientific reports Sep 9, 2024
Recent developments in Deep Learning have opened the possibility for automated segmentation of large and highly detailed CT scan datasets of fossil material. However, previous methodologies have required large amounts of training data to reliably ext...
Image Processing, Computer-Assisted Tomography, X-Ray Computed Animals Fossils Deep Learning Imaging, Three-Dimensional
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Integrating Clinical Data and Radiomics and Deep Learning Features for End-to-End Delayed Cerebral Ischemia Prediction on Noncontrast CT.

AJNR. American journal of neuroradiology Sep 9, 2024
BACKGROUND AND PURPOSE: Delayed cerebral ischemia is hard to diagnose early due to gradual, symptomless development. This study aimed to develop an automated model for predicting delayed cerebral ischemia following aneurysmal SAH on NCCT.
Female Aged Adult Humans Retrospective Studies Tomography, X-Ray Computed Deep Learning Predictive Value of Tests Brain Ischemia Radiomics Male Middle Aged
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MR Cranial Bone Imaging: Evaluation of Both Motion-Corrected and Automated Deep Learning Pseudo-CT Estimated MR Images.

AJNR. American journal of neuroradiology Sep 9, 2024
BACKGROUND AND PURPOSE: CT imaging exposes patients to ionizing radiation. MR imaging is radiation free but previously has not been able to produce diagnostic-quality images of bone on a timeline suitable for clinical use. We developed automated moti...
Humans Child, Preschool Child Magnetic Resonance Imaging Male Tomography, X-Ray Computed Deep Learning Female Skull Adolescent Sensitivity and Specificity Cranial Sutures Skull Fractures Motion
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Assessing the Performance of Artificial Intelligence Models: Insights from the American Society of Functional Neuroradiology Artificial Intelligence Competition.

AJNR. American journal of neuroradiology Sep 9, 2024
BACKGROUND AND PURPOSE: Artificial intelligence models in radiology are frequently developed and validated using data sets from a single institution and are rarely tested on independent, external data sets, raising questions about their generalizabil...
Female Reproducibility of Results Middle Aged Aged United States Humans Adult Young Adult Brain Diseases Artificial Intelligence Sensitivity and Specificity Societies, Medical Tomography, X-Ray Computed Male
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