AIMC Topic: Deep Learning

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A Pilot Study on Convolutional Neural Networks for Motion Estimation From Ultrasound Images.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
In recent years, deep learning (DL) has been successfully applied to the analysis and processing of ultrasound images. To date, most of this research has focused on segmentation and view recognition. This article benchmarks different convolutional ne...

Displacement Estimation in Ultrasound Elastography Using Pyramidal Convolutional Neural Network.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
In this article, two novel deep learning methods are proposed for displacement estimation in ultrasound elastography (USE). Although convolutional neural networks (CNNs) have been very successful for displacement estimation in computer vision, they h...

Deep Learning for US Image Quality Assessment Based on Femoral Cartilage Boundary Detection in Autonomous Knee Arthroscopy.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Knee arthroscopy is a complex minimally invasive surgery that can cause unintended injuries to femoral cartilage or postoperative complications, or both. Autonomous robotic systems using real-time volumetric ultrasound (US) imaging guidance hold pote...

A Deep Learning Approach to Photoacoustic Wavefront Localization in Deep-Tissue Medium.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Optical photons undergo strong scattering when propagating beyond 1-mm deep inside biological tissue. Finding the origin of these diffused optical wavefronts is a challenging task. Breaking through the optical diffusion limit, photoacoustic (PA) imag...

Internet of Medical Things: An Effective and Fully Automatic IoT Approach Using Deep Learning and Fine-Tuning to Lung CT Segmentation.

Sensors (Basel, Switzerland)
Several pathologies have a direct impact on society, causing public health problems. Pulmonary diseases such as Chronic obstructive pulmonary disease (COPD) are already the third leading cause of death in the world, leaving tuberculosis at ninth with...

Artificial intelligence algorithm for detecting myocardial infarction using six-lead electrocardiography.

Scientific reports
Rapid diagnosis of myocardial infarction (MI) using electrocardiography (ECG) is the cornerstone of effective treatment and prevention of mortality; however, conventional interpretation methods has low reliability for detecting MI and is difficulty t...

Deep convolution neural networks based artifact suppression in under-sampled radial acquisitions of myocardial T mapping images.

Physics in medicine and biology
We developed a deep convolutional neural network (CNN) based method to remove streaking artefact from accelerated radial acquisitions of myocardial T -mapping images. A deep CNN based on a modified U-Net architecture was developed and trained to remo...

Artificial intelligence in image reconstruction: The change is here.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Innovations in CT have been impressive among imaging and medical technologies in both the hardware and software domain. The range and speed of CT scanning improved from the introduction of multidetector-row CT scanners with wide-array detectors and f...

Clinical Named Entity Recognition from Chinese Electronic Medical Records Based on Deep Learning Pretraining.

Journal of healthcare engineering
BACKGROUND: Clinical named entity recognition is the basic task of mining electronic medical records text, which are with some challenges containing the language features of Chinese electronic medical records text with many compound entities, serious...