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ACSwinNet: A Deep Learning-Based Rigid Registration Method for Head-Neck CT-CBCT Images in Image-Guided Radiotherapy.

Sensors (Basel, Switzerland)
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...

Automatic localization of anatomical landmarks in head cine fluoroscopy images via deep learning.

Medical physics
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...

MUsculo-Skeleton-Aware (MUSA) deep learning for anatomically guided head-and-neck CT deformable registration.

Medical image analysis
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...

Deep Learning Approaches for the Assessment of Germinal Matrix Hemorrhage Using Neonatal Head Ultrasound.

Sensors (Basel, Switzerland)
Germinal matrix hemorrhage (GMH) is a critical condition affecting premature infants, commonly diagnosed through cranial ultrasound imaging. This study presents an advanced deep learning approach for automated GMH grading using the YOLOv8 model. By a...

Image-based Artificial Intelligence models in the diagnosis and classification of vascular anomalies of the soft tissue in the head and neck.

Computer methods and programs in biomedicine
BACKGROUND: The International Society for the Study of Vascular Anomalies (ISSVA) provides a detailed classification system to facilitate accurate diagnosis and management of these conditions based on clinical criteria, imaging, and histopathological...

Brain-wide neural recordings in mice navigating physical spaces enabled by robotic neural recording headstages.

Nature methods
Technologies that can record neural activity at cellular resolution at multiple spatial and temporal scales are typically much larger than the animals that are being recorded from and are thus limited to recording from head-fixed subjects. Here we ha...

OperaGAN: A simultaneous transfer network for opera makeup and complex headwear.

Neural networks : the official journal of the International Neural Network Society
Standard makeup transfer techniques mainly focus on facial makeup. The texture details of headwear in style examples tend to be ignored. When dealing with complex portrait style transfer, simultaneous correct headwear and facial makeup transfer often...

Machine learning model to study the rugby head impact in a laboratory setting.

PloS one
The incidence of head impacts in rugby has been a growing concern for player safety. While rugby headgear shows potential to mitigate head impact intensity during laboratory simulations, evaluating its on-field effectiveness is challenging. Current r...

Machine learning-based estimation of respiratory fluctuations in a healthy adult population using resting state BOLD fMRI and head motion parameters.

Magnetic resonance in medicine
PURPOSE: External physiological monitoring is the primary approach to measure and remove effects of low-frequency respiratory variation from BOLD-fMRI signals. However, the acquisition of clean external respiratory data during fMRI is not always poss...