Pregnancy

A Human Microrobot Interface Based on Acoustic Manipulation.

Micro/nanorobotic systems capable of targeted transporting and releasing hold considerable promise for drug delivery, cellular surgery, biosensing, nano assembling, . However, on-demand precise control of the micro/nanorobot movement remains a major challenge. In particular, a practical interface to realize instant and customized interactions between human and micro/nanorobots, which is quite esse...

Deeply-Supervised Networks With Threshold Loss for Cancer Detection in Automated Breast Ultrasound.

ABUS, or Automated breast ultrasound, is an innovative and promising method of screening for breast examination. Comparing to common B-mode 2D ultrasound, ABUS attains operator-independent image acquisition and also provides 3D views of the whole breast. Nonetheless, reviewing ABUS images is particularly time-intensive and errors by oversight might occur. For this study, we offer an innovative 3D ...

Localizing B-Lines in Lung Ultrasonography by Weakly Supervised Deep Learning, In-Vivo Results.

Lung ultrasound (LUS) is nowadays gaining growing attention from both the clinical and technical world. Of particular interest are several imaging-art...

Semiautomatic Fetal Intelligent Navigation Echocardiography Has the Potential to Aid Cardiac Evaluations Even in Less Experienced Hands.

OBJECTIVES: To investigate the interobserver and intraobserver variability and corresponding learning curve in a semiautomatic approach for a standard...

Improving realism in patient-specific abdominal ultrasound simulation using CycleGANs.

PURPOSE: In this paper, we propose to apply generative adversarial neural networks trained with a cycle consistency loss, or CycleGANs, to improve rea...

How and why should the radiologist look at the placenta?

This editorial comment refers to the article "Identification of suspicious invasive placentation based on clinical MRI data using textural features an...

Social Media Surveillance of Multiple Sclerosis Medications Used During Pregnancy and Breastfeeding: Content Analysis.

BACKGROUND: Multiple sclerosis (MS) is a chronic neurological disease occurring mostly in women of childbearing age. Pregnant women with MS are usuall...

Performance of machine learning software to classify breast lesions using BI-RADS radiomic features on ultrasound images.

BACKGROUND: The purpose of this work was to evaluate computable Breast Imaging Reporting and Data System (BI-RADS) radiomic features to classify breas...

Self-supervised learning for medical image analysis using image context restoration.

Machine learning, particularly deep learning has boosted medical image analysis over the past years. Training a good model based on deep learning requ...

Evaluation of machine learning methods with Fourier Transform features for classifying ovarian tumors based on ultrasound images.

INTRODUCTION: Ovarian tumors are the most common diagnostic challenge for gynecologists and ultrasound examination has become the main technique for a...

A Deep Learning Framework for Single-Sided Sound Speed Inversion in Medical Ultrasound.

OBJECTIVE: Ultrasound elastography is gaining traction as an accessible and useful diagnostic tool for things such as, cancer detection and differenti...

Modeling azo dye removal by sono-fenton processes using response surface methodology and artificial neural network approaches.

Textile industry wastewaters, which cause serious problems in the environment and human health, include synthetic dyes, complex organic pollutants, su...

Validation of radiologists' findings by computer-aided detection (CAD) software in breast cancer detection with automated 3D breast ultrasound: a concept study in implementation of artificial intelligence software.

BACKGROUND: Computer-aided detection software for automated breast ultrasound has been shown to have potential in improving the accuracy of radiologis...

Learning the implicit strain reconstruction in ultrasound elastography using privileged information.

Quasi-static ultrasound elastography is an importance imaging technology to assess the conditions of various diseases through reconstructing the tissu...

Accurate and robust deep learning-based segmentation of the prostate clinical target volume in ultrasound images.

The goal of this work was to develop a method for accurate and robust automatic segmentation of the prostate clinical target volume in transrectal ult...

Assessing micrometastases as a target for nanoparticles using 3D microscopy and machine learning.

Metastasis of solid tumors is a key determinant of cancer patient survival. Targeting micrometastases using nanoparticles could offer a way to stop me...

Classification of Carotid Artery Intima Media Thickness Ultrasound Images with Deep Learning.

Cerebrovascular accident due to carotid artery disease is the most common cause of death in developed countries following heart disease and cancer. Fo...

Deep visual nerve tracking in ultrasound images.

Ultrasound-guided regional anesthesia (UGRA) becomes a standard procedure in surgical operations and pain management, offers the advantages of nerve l...

Automatic evaluation of fetal head biometry from ultrasound images using machine learning.

OBJECTIVE: Ultrasound-based fetal biometric measurements, such as head circumference (HC) and biparietal diameter (BPD), are frequently used to evalua...

Improved Deep Learning Network Based in combination with Cost-sensitive Learning for Early Detection of Ovarian Cancer in Color Ultrasound Detecting System.

With the development of theories and technologies in medical imaging, most of the tumors can be detected in the early stage. However, the nature of ov...