AIMC Journal:
BMC medical imaging

Showing 201 to 210 of 252 articles

External validation study on the value of deep learning algorithm for the prediction of hematoma expansion from noncontrast CT scans.

BMC medical imaging Mar 14, 2022
BACKGROUND: Hematoma expansion is an independent predictor of patient outcome and mortality. The early diagnosis of hematoma expansion is crucial for selecting clinical treatment options. This study aims to explore the value of a deep learning algori...
Tomography, X-Ray Computed Deep Learning Hematoma Artificial Intelligence Cerebral Hemorrhage Humans Retrospective Studies
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Automated detection of pulmonary embolism from CT-angiograms using deep learning.

BMC medical imaging Mar 14, 2022
BACKGROUND: The aim of this study was to develop and evaluate a deep neural network model in the automated detection of pulmonary embolism (PE) from computed tomography pulmonary angiograms (CTPAs) using only weakly labelled training data.
Deep Learning Pulmonary Embolism Angiography Retrospective Studies Tomography, X-Ray Computed Humans
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A deep learning framework for automated detection and quantitative assessment of liver trauma.

BMC medical imaging Mar 8, 2022
BACKGROUND: Both early detection and severity assessment of liver trauma are critical for optimal triage and management of trauma patients. Current trauma protocols utilize computed tomography (CT) assessment of injuries in a subjective and qualitati...
Deep Learning Image Processing, Computer-Assisted Liver Neural Networks, Computer Tomography, X-Ray Computed Humans
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Grayscale medical image segmentation method based on 2D&3D object detection with deep learning.

BMC medical imaging Feb 27, 2022
BACKGROUND: Grayscale medical image segmentation is the key step in clinical computer-aided diagnosis. Model-driven and data-driven image segmentation methods are widely used for their less computational complexity and more accurate feature extractio...
Deep Learning Image Processing, Computer-Assisted Humans Diagnosis, Computer-Assisted
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Artificial intelligence stenosis diagnosis in coronary CTA: effect on the performance and consistency of readers with less cardiovascular experience.

BMC medical imaging Feb 17, 2022
BACKGROUND: To investigate the influence of artificial intelligence (AI) based on deep learning on the diagnostic performance and consistency of inexperienced cardiovascular radiologists.
Coronary Angiography Artificial Intelligence Observer Variation Humans Area Under Curve Retrospective Studies Aged Computed Tomography Angiography Coronary Stenosis Middle Aged Deep Learning Sensitivity and Specificity Clinical Competence
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The application research of AI image recognition and processing technology in the early diagnosis of the COVID-19.

BMC medical imaging Feb 17, 2022
BACKGROUND: This study intends to establish a combined prediction model that integrates the clinical symptoms,the lung lesion volume, and the radiomics features of patients with COVID-19, resulting in a new model to predict the severity of COVID-19.
Adult Male Early Diagnosis Retrospective Studies Humans Middle Aged Female Aged Artificial Intelligence COVID-19
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Clinical language search algorithm from free-text: facilitating appropriate imaging.

BMC medical imaging Feb 4, 2022
BACKGROUND: The comprehensiveness and maintenance of the American College of Radiology (ACR) Appropriateness Criteria (AC) makes it a unique resource for evidence-based clinical imaging decision support, but it is underutilized by clinicians. To faci...
Young Adult Adult Male Female Aged Natural Language Processing Diagnostic Imaging Radiology Middle Aged Adolescent Humans Semantics Search Engine
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Vessel segmentation for X-ray coronary angiography using ensemble methods with deep learning and filter-based features.

BMC medical imaging Jan 19, 2022
BACKGROUND: Automated segmentation of coronary arteries is a crucial step for computer-aided coronary artery disease (CAD) diagnosis and treatment planning. Correct delineation of the coronary artery is challenging in X-ray coronary angiography (XCA)...
Coronary Disease Image Processing, Computer-Assisted Humans Coronary Angiography Deep Learning Coronary Vessels
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Self-relabeling for noise-tolerant retina vessel segmentation through label reliability estimation.

BMC medical imaging Jan 12, 2022
BACKGROUND: Retinal vessel segmentation benefits significantly from deep learning. Its performance relies on sufficient training images with accurate ground-truth segmentation, which are usually manually annotated in the form of binary pixel-wise lab...
Retinal Vessels Humans Image Processing, Computer-Assisted Deep Learning Artifacts
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Deep learning-based pancreas volume assessment in individuals with type 1 diabetes.

BMC medical imaging Jan 5, 2022
Pancreas volume is reduced in individuals with diabetes and in autoantibody positive individuals at high risk for developing type 1 diabetes (T1D). Studies investigating pancreas volume are underway to assess pancreas volume in large clinical databas...
Pancreas Magnetic Resonance Imaging Algorithms Organ Size Retrospective Studies Male Imaging, Three-Dimensional Deep Learning Humans Image Processing, Computer-Assisted Adolescent Diabetes Mellitus, Type 1
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