AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Phantoms, Imaging

Showing 341 to 350 of 748 articles

Clear Filters

Native-resolution myocardial principal Eulerian strain mapping using convolutional neural networks and Tagged Magnetic Resonance Imaging.

Computers in biology and medicine
BACKGROUND: Assessment of regional myocardial function at native pixel-level resolution can play a crucial role in recognizing the early signs of the decline in regional myocardial function. Extensive data processing in existing techniques limits the...

Enabling quantitative robot-assisted compressional elastography via the extended Kalman filter.

Physics in medicine and biology
Compressional or quasi-static elastography has demonstrated the capability to detect occult cancers in a variety of tissue types, however it has a serious limitation in that the resulting elastograms are generally qualitative whereas other forms of e...

Low-dose CT reconstruction with Noise2Noise network and testing-time fine-tuning.

Medical physics
PURPOSE: Deep learning-based image denoising and reconstruction methods demonstrated promising performance on low-dose CT imaging in recent years. However, most existing deep learning-based low-dose CT reconstruction methods require normal-dose image...

Ultrasound deep learning for monitoring of flow-vessel dynamics in murine carotid artery.

Ultrasonics
Several arterial diseases are closely related with mechanical properties of the blood vessel and interactions of flow-vessel dynamics such as mean flow velocity, wall shear stress (WSS) and vascular strain. However, there is an opportunity to improve...

Evaluation of a custom-designed human-robot collaboration control system for dental implant robot.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: The purpose of this study is to develop a methodology to better control a human-robot collaboration for robotic dental implant placement. We have designed a human-robot collaborative implant system (HRCDIS) which is based on a zero-force ...

Deep Learning for Ultrasound Beamforming in Flexible Array Transducer.

IEEE transactions on medical imaging
Ultrasound imaging has been developed for image-guided radiotherapy for tumor tracking, and the flexible array transducer is a promising tool for this task. It can reduce the user dependence and anatomical changes caused by the traditional ultrasound...

Real-time 3D motion estimation from undersampled MRI using multi-resolution neural networks.

Medical physics
PURPOSE: To enable real-time adaptive magnetic resonance imaging-guided radiotherapy (MRIgRT) by obtaining time-resolved three-dimensional (3D) deformation vector fields (DVFs) with high spatiotemporal resolution and low latency (  ms). Theory and M...

Faster super-resolution ultrasound imaging with a deep learning model for tissue decluttering and contrast agent localization.

Biomedical physics & engineering express
Super-resolution ultrasound (SR-US) imaging allows visualization of microvascular structures as small as tens of micrometers in diameter. However, use in the clinical setting has been impeded in part by ultrasound (US) acquisition times exceeding a b...

A convolutional neural network for estimating cone-beam CT intensity deviations from virtual CT projections.

Physics in medicine and biology
Extending cone-beam CT (CBCT) use toward dose accumulation and adaptive radiotherapy (ART) necessitates more accurate HU reproduction since cone-beam geometries are heavily degraded by photon scatter. This study proposes a novel method which aims to ...

Classification of moving coronary calcified plaques based on motion artifacts using convolutional neural networks: a robotic simulating study on influential factors.

BMC medical imaging
BACKGROUND: Motion artifacts affect the images of coronary calcified plaques. This study utilized convolutional neural networks (CNNs) to classify the motion-contaminated images of moving coronary calcified plaques and to determine the influential fa...