AI Medical Compendium Topic:
Motion

Clear Filters Showing 731 to 740 of 846 articles

Mandarin Speech Reconstruction from Tongue Motion Ultrasound Images based on Generative Adversarial Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Speech impairment resulting from laryngectomy causes severe physiological and psychological distress to laryngectomee. In clinical practice, the upper vocal tract articulatory organs function normally in most laryngectomee. The potential to reconstru...

Deep Left Ventricular Motion Estimation Methods in Echocardiography: A Comparative Study.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Motion estimation in echocardiography is critical when assessing heart function and calculating myocardial deformation indices. Nevertheless, there are limitations in clinical practice, particularly with regard to the accuracy and reliability of meas...

Magnetic motors in interphases: Motion control and integration in soft robots.

Biointerphases
Magnetic motors are a class of out-of-equilibrium particles that exhibit controlled and fast motion overcoming Brownian fluctuations by harnessing external magnetic fields. The advances in this field resulted in motors that have been used for differe...

[A deep blur learning-based motion artifact reduction algorithm for dental cone-beam computed tomography images].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University
OBJECTIVE: We propose a motion artifact correction algorithm (DMBL) for reducing motion artifacts in reconstructed dental cone-beam computed tomography (CBCT) images based on deep blur learning.

A back propagation neural network based respiratory motion modelling method.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: This study presents the development of a backpropagation neural network-based respiratory motion modelling method (BP-RMM) for precisely tracking arbitrary points within lung tissue throughout free respiration, encompassing deep inspirati...

Improving Image Quality and Diagnostic Performance of CCTA in Patients with Challenging Heart Rate Conditions using a Deep Learning-based Motion Correction Algorithm.

Current medical imaging
OBJECTIVE: Challenging HR conditions, such as elevated Heart Rate (HR) and Heart Rate Variability (HRV), are major contributors to motion artifacts in Coronary Computed Tomography Angiography (CCTA). This study aims to assess the impact of a deep lea...

OctoShaker: A versatile robotic biomechanical agitator for cellular and organoid research.

The Review of scientific instruments
Mechanical forces have increasingly been recognized as a key regulator in the fate of cellular development and functionality. Different mechanical transduction methods, such as substrate stiffness and magnetic bead vibration, have been experimented w...

Comparison of Admittance Control Dynamic Models for Transparent Free-Motion Human-Robot Interaction.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
This paper presents an experimental comparison of multiple admittance control dynamic models implemented on a five-degree-of-freedom arm exoskeleton. The performance of each model is evaluated for transparency, stability, and impact on point-to-point...

Musculoskeletal CT Imaging: State-of-the-Art Advancements and Future Directions.

Radiology
CT is one of the most widely used modalities for musculoskeletal imaging. Recent advancements in the field include the introduction of four-dimensional CT, which captures a CT image during motion; cone-beam CT, which uses flat-panel detectors to capt...

Research on motion recognition based on multi-dimensional sensing data and deep learning algorithms.

Mathematical biosciences and engineering : MBE
Motion recognition provides movement information for people with physical dysfunction, the elderly and motion-sensing games production, and is important for accurate recognition of human motion. We employed three classical machine learning algorithms...