AIMC Topic: Imaging, Three-Dimensional

Clear Filters Showing 781 to 790 of 1894 articles

Multi-Objective Location and Mapping Based on Deep Learning and Visual Slam.

Sensors (Basel, Switzerland)
Simultaneous localization and mapping (SLAM) technology can be used to locate and build maps in unknown environments, but the constructed maps often suffer from poor readability and interactivity, and the primary and secondary information in the map ...

Accelerated 4D-flow MRI with 3-point encoding enabled by machine learning.

Magnetic resonance in medicine
PURPOSE: To investigate the acceleration of 4D-flow MRI using a convolutional neural network (CNN) that produces three directional velocities from three flow encodings, without requiring a fourth reference scan measuring background phase.

CAR-Net: A Deep Learning-Based Deformation Model for 3D/2D Coronary Artery Registration.

IEEE transactions on medical imaging
Percutaneous coronary intervention is widely applied for the treatment of coronary artery disease under the guidance of X-ray coronary angiography (XCA) image. However, the projective nature of XCA causes the loss of 3D structural information, which ...

Feasibility of a Robot-Assisted Surgical Navigation System for Mandibular Distraction Osteogenesis in Hemifacial Microsomia: A Model Experiment.

The Journal of craniofacial surgery
This study aimed to investigate the feasibility and accuracy of osteotomy and distractor placement using a robotic navigation system in a model surgical experiment of mandibular distraction osteogenesis for hemifacial microsomia. Imaging data from 5 ...

A coarse-to-fine cascade deep learning neural network for segmenting cerebral aneurysms in time-of-flight magnetic resonance angiography.

Biomedical engineering online
BACKGROUND: Accurate segmentation of unruptured cerebral aneurysms (UCAs) is essential to treatment planning and rupture risk assessment. Currently, three-dimensional time-of-flight magnetic resonance angiography (3D TOF-MRA) has been the most common...

TransMorph: Transformer for unsupervised medical image registration.

Medical image analysis
In the last decade, convolutional neural networks (ConvNets) have been a major focus of research in medical image analysis. However, the performances of ConvNets may be limited by a lack of explicit consideration of the long-range spatial relationshi...

Automated analysis of three-dimensional CBCT images taken in natural head position that combines facial profile processing and multiple deep-learning models.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Analyzing three-dimensional cone beam computed tomography (CBCT) images has become an indispensable procedure for diagnosis and treatment planning of orthodontic patients. Artificial intelligence, especially deep-learning t...

A Review of Multi-Modal Learning from the Text-Guided Visual Processing Viewpoint.

Sensors (Basel, Switzerland)
For decades, co-relating different data domains to attain the maximum potential of machines has driven research, especially in neural networks. Similarly, text and visual data (images and videos) are two distinct data domains with extensive research ...

Three-Dimensional Reconstruction of National Traditional Sports Cultural Heritage Based on Feature Clustering and Artificial Intelligence.

Computational intelligence and neuroscience
The development of three-dimensional reconstruction technology with cultural heritage in traditional sports allows an accurate portrayal of this aspect of life. Cultural heritage can be documented, recovered, and shown with the tools and techniques. ...

Femoral image segmentation based on two-stage convolutional network using 3D-DMFNet and 3D-ResUnet.

Computer methods and programs in biomedicine
OBJECTIVE: The femur is a typical human long bone with an irregular spatial structure. Femoral fractures are the most common occurrence in middle-aged and older adults. The structure of human bone tissue is very complex, and there are significant dif...