AIMC Topic: Imaging, Three-Dimensional

Clear Filters Showing 441 to 450 of 1894 articles

Modeling 3D Cardiac Contraction and Relaxation With Point Cloud Deformation Networks.

IEEE journal of biomedical and health informatics
Global single-valued biomarkers, such as ejection fraction, are widely used in clinical practice to assess cardiac function. However, they only approximate the heart's true 3D deformation process, thus limiting diagnostic accuracy and the understandi...

3-D Quantum-Inspired Self-Supervised Tensor Network for Volumetric Segmentation of Medical Images.

IEEE transactions on neural networks and learning systems
This article introduces a novel shallow 3-D self-supervised tensor neural network in quantum formalism for volumetric segmentation of medical images with merits of obviating training and supervision. The proposed network is referred to as the 3-D qua...

Estimating three-dimensional foot bone kinematics from skin markers using a deep learning neural network model.

Journal of biomechanics
The human foot is a complex structure comprising 26 bones, whose coordinated movements facilitate proper deformation of the foot, ensuring stable and efficient locomotion. Despite their critical role, the kinematics of foot bones during movement rema...

MSRA-Net: multi-channel semantic-aware and residual attention mechanism network for unsupervised 3D image registration.

Physics in medicine and biology
. Convolutional neural network (CNN) is developing rapidly in the field of medical image registration, and the proposed U-Net further improves the precision of registration. However, this method may discard certain important information in the proces...

Improving 3D dose prediction for breast radiotherapy using novel glowing masks and gradient-weighted loss functions.

Medical physics
BACKGROUND: The quality of treatment plans for breast cancer can vary greatly. This variation could be reduced by using dose prediction to automate treatment planning. Our work investigates novel methods for training deep-learning models that are cap...

Improved microvascular imaging with optical coherence tomography using 3D neural networks and a channel attention mechanism.

Scientific reports
Skin microvasculature is vital for human cardiovascular health and thermoregulation, but its imaging and analysis presents significant challenges. Statistical methods such as speckle decorrelation in optical coherence tomography angiography (OCTA) of...

Protocol for machine-learning-based 3D image analysis of nuclear envelope tubules in cultured cells.

STAR protocols
The nuclear envelope can form complex structures in physiological and pathological contexts. Current approaches to quantify nuclear envelope structures can be time-consuming or inaccurate. Here, we present a protocol to measure nuclear envelope tubul...

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
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...

Automatic robotic doppler sonography of leg arteries.

International journal of computer assisted radiology and surgery
PURPOSE: Robot-assisted systems offer an opportunity to support the diagnostic and therapeutic treatment of vascular diseases to reduce radiation exposure and support the limited medical staff in vascular medicine. In the diagnosis and follow-up care...