Deep-learning-based deformable image registration (DL-DIR) has demonstrated improved accuracy compared to time-consuming non-DL methods across various anatomical sites. However, DL-DIR is still challenging in heterogeneous tissue regions with large d...
Diagnostic and interventional imaging
Sep 19, 2024
PURPOSE: The purpose of this study was to investigate the added value of artificial intelligence (AI) solutions for the detection of arterial stenosis (AS) on head and neck CT angiography (CTA).
Accurate and precise rigid registration between head-neck computed tomography (CT) and cone-beam computed tomography (CBCT) images is crucial for correcting setup errors in image-guided radiotherapy (IGRT) for head and neck tumors. However, conventio...
IEEE transactions on bio-medical engineering
Aug 21, 2024
OBJECTIVE: Wearable devices are developed to measure head impact kinematics but are intrinsically noisy because of the imperfect interface with human bodies. This study aimed to improve the head impact kinematics measurements obtained from instrument...
BACKGROUND: Fluoroscopy guided interventions (FGIs) pose a risk of prolonged radiation exposure; personalized patient dosimetry is necessary to improve patient safety during these procedures. However, current FGIs systems do not capture the precise e...
BACKGROUND: The volume measurement of intracerebral hemorrhage (ICH) and intraventricular hemorrhage (IVH) provides critical information for precise treatment of patients with spontaneous ICH but remains a big challenge, especially for IVH segmentati...
European journal of obstetrics, gynecology, and reproductive biology
Aug 9, 2024
OBJECTIVES: To develop a deep learning (DL)-model using convolutional neural networks (CNN) to automatically identify the fetal head position at transperineal ultrasound in the second stage of labor.
INTRODUCTION: Diagnostic imaging is vital in emergency departments (EDs). Accessibility and reporting impacts ED workflow and patient care. With radiology workforce shortages, reporting capacity is limited, leading to image interpretation delays. Tur...
International journal of medical informatics
Jun 13, 2024
BACKGROUND: The surge in emergency head CT imaging and artificial intelligence (AI) advancements, especially deep learning (DL) and convolutional neural networks (CNN), have accelerated the development of computer-aided diagnosis (CADx) for emergency...
In this retrospective study, we aimed to assess the objective and subjective image quality of different reconstruction techniques and a deep learning-based software on non-contrast head computed tomography (CT) images. In total, 152 adult head CT sca...
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