AIMC Topic: Radiographic Image Interpretation, Computer-Assisted

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A Deep Learning Method for Pneumonia Detection Based on Fuzzy Non-Maximum Suppression.

IEEE/ACM transactions on computational biology and bioinformatics Aug 8, 2024
Pneumonia is one of the largest causes of death in the world. Deep learning techniques can assist doctors to detect the areas of pneumonia in the chest X-rays images. However, existing methods lack sufficient consideration for the large variation sca...
Humans Algorithms Deep Learning Fuzzy Logic Pneumonia Radiographic Image Interpretation, Computer-Assisted Radiography, Thoracic
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A Deep Learning Approach Considering Image Background for Pneumonia Identification Using Explainable AI (XAI).

IEEE/ACM transactions on computational biology and bioinformatics Aug 8, 2024
Pneumonia mainly refers to lung infections caused by pathogens, such as bacteria and viruses. Currently, deep learning methods have been applied to identify pneumonia. However, the traditional deep learning methods for pneumonia identification take l...
Radiographic Image Interpretation, Computer-Assisted Humans Algorithms Lung Deep Learning Pneumonia
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Ensemble machine learning to predict futile recanalization after mechanical thrombectomy based on non-contrast CT imaging.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Aug 6, 2024
OBJECTIVES: Despite successful recanalization after Mechanical Thrombectomy (MT), approximately 25 % of patients with Acute Ischemic Stroke (AIS) due to Large Vessel Occlusion (LVO) show unfavorable clinical outcomes, namely Futile Recanalization (FR...
Machine Learning Decision Support Techniques Retrospective Studies Tomography, X-Ray Computed Humans Aged, 80 and over Male Middle Aged Risk Assessment Time Factors Clinical Decision-Making Female Risk Factors Aged Infarction, Middle Cerebral Artery Thrombectomy Medical Futility Treatment Outcome Predictive Value of Tests Ischemic Stroke Radiographic Image Interpretation, Computer-Assisted
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Precision and Robust Models on Healthcare Institution Federated Learning for Predicting HCC on Portal Venous CT Images.

IEEE journal of biomedical and health informatics Aug 6, 2024
Hepatocellular carcinoma (HCC), the most common type of liver cancer, poses significant challenges in detection and diagnosis. Medical imaging, especially computed tomography (CT), is pivotal in non-invasively identifying this disease, requiring subs...
Deep Learning Liver Neoplasms Carcinoma, Hepatocellular Radiographic Image Interpretation, Computer-Assisted Portal Vein Humans Algorithms Tomography, X-Ray Computed
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Automated detection and classification of mandibular fractures on multislice spiral computed tomography using modified convolutional neural networks.

Oral surgery, oral medicine, oral pathology and oral radiology Aug 5, 2024
OBJECTIVE: To evaluate the performance of convolutional neural networks (CNNs) for the automated detection and classification of mandibular fractures on multislice spiral computed tomography (MSCT).
Tomography, Spiral Computed Mandibular Fractures Middle Aged Adolescent Radiographic Image Interpretation, Computer-Assisted Multidetector Computed Tomography Humans Neural Networks, Computer Retrospective Studies Adult Female Sensitivity and Specificity Male Aged
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Performance of AI for preoperative CT assessment of lung metastases: Retrospective analysis of 167 patients.

European journal of radiology Aug 3, 2024
OBJECTIVES: To evaluate the performance of artificial intelligence (AI) in the preoperative detection of lung metastases on CT.
Lung Neoplasms Radiographic Image Interpretation, Computer-Assisted Preoperative Care Retrospective Studies Tomography, X-Ray Computed Female Aged Sensitivity and Specificity Male Middle Aged Lung Humans Artificial Intelligence
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Effect of Deep Learning Image Reconstruction Algorithms on Radiomic Features of Pulmonary Nodules in Ultra-Low-Dose CT.

Journal of computer assisted tomography Aug 2, 2024
OBJECTIVE: The purpose of this study is to explore the impact of deep learning image reconstruction (DLIR) algorithm on the quantification of radiomic features in ultra-low-dose computed tomography (ULD-CT) compared with adaptive statistical iterativ...
Lung Neoplasms Multiple Pulmonary Nodules Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Male Middle Aged Lung Deep Learning Algorithms Humans Retrospective Studies Radiation Dosage Tomography, X-Ray Computed Female Reproducibility of Results Aged Adult Radiomics
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Clinical feasibility of deep learning based synthetic contrast enhanced abdominal CT in patients undergoing non enhanced CT scans.

Scientific reports Jul 31, 2024
Our objective was to develop and evaluate the clinical feasibility of deep-learning-based synthetic contrast-enhanced computed tomography (DL-SynCCT) in patients designated for nonenhanced CT (NECT). We proposed a weakly supervised learning with the ...
Contrast Media Radiographic Image Interpretation, Computer-Assisted Feasibility Studies Radiography, Abdominal Male Humans Middle Aged Deep Learning Retrospective Studies Abdomen Tomography, X-Ray Computed Female Aged Aged, 80 and over Adult
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Image Quality Assessment of a Deep Learning-Based Automatic Bone Removal Algorithm for Cervical CTA.

Journal of computer assisted tomography Jul 30, 2024
BACKGROUND: The present study aims to evaluate the postprocessing image quality of a deep-learning (DL)-based automatic bone removal algorithm in the real clinical practice for cervical computed tomography angiography (CTA).
Neck Radiographic Image Interpretation, Computer-Assisted Aged Carotid Arteries Humans Carotid Stenosis Computed Tomography Angiography Male Algorithms Middle Aged Retrospective Studies Deep Learning Female
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Deep Learning Based Automatic Segmentation of the Thoracic Aorta from Chest Computed Tomography in Healthy Korean Adults.

European journal of vascular and endovascular surgery : the official journal of the European Society for Vascular Surgery Jul 30, 2024
OBJECTIVE: Segmenting the aorta into zones based on anatomical landmarks is a current trend to better understand interventions for aortic dissection or aneurysm. However, comprehensive reference values for aortic zones are lacking. The aim of this st...
Male Aortography Radiographic Image Interpretation, Computer-Assisted Middle Aged Humans Republic of Korea Reference Values Deep Learning Retrospective Studies Female Healthy Volunteers Imaging, Three-Dimensional Tomography, X-Ray Computed Aged Aorta, Thoracic Adult
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