Pregnancy

Automatic and accurate needle detection in 2D ultrasound during robot-assisted needle insertion process.

PURPOSE: Robot-assisted needle insertion guided by 2D ultrasound (US) can effectively improve the accuracy and success rate of clinical puncture. To this end, automatic and accurate needle-tracking methods are important for monitoring puncture processes, avoiding the needle deviating from the intended path, and reducing the risk of injury to surrounding tissues. This work aims to develop a framewo...

Comparing deep learning-based automatic segmentation of breast masses to expert interobserver variability in ultrasound imaging.

Deep learning is a powerful tool that became practical in 2008, harnessing the power of Graphic Processing Unites, and has developed rapidly in image, video, and natural language processing. There are ongoing developments in the application of deep learning to medical data for a variety of tasks across multiple imaging modalities. The reliability and repeatability of deep learning techniques are o...

Environmentally Adaptive Shape-Morphing Microrobots for Localized Cancer Cell Treatment.

Microrobots have attracted considerable attention due to their extensive applications in microobject manipulation and targeted drug delivery. To reali...

Exploring a new paradigm for the fetal anomaly ultrasound scan: Artificial intelligence in real time.

OBJECTIVE: Advances in artificial intelligence (AI) have demonstrated potential to improve medical diagnosis. We piloted the end-to-end automation of ...

Can artificial intelligence replace ultrasound as a complementary tool to mammogram for the diagnosis of the breast cancer?

OBJECTIVE: To study the impact of artificial intelligence (AI) on the performance of mammogram with regard to the classification of the detected breas...

Automatic identification of triple negative breast cancer in ultrasonography using a deep convolutional neural network.

Triple negative (TN) breast cancer is a subtype of breast cancer which is difficult for early detection and the prognosis is poor. In this paper, 910 ...

Ultrasound Images Guided under Deep Learning in the Anesthesia Effect of the Regional Nerve Block on Scapular Fracture Surgery.

In order to discuss the clinical characteristics of patients with scapular fracture, deep learning model was adopted in ultrasound images of patients ...

Multi-Source Transfer Learning Via Multi-Kernel Support Vector Machine Plus for B-Mode Ultrasound-Based Computer-Aided Diagnosis of Liver Cancers.

B-mode ultrasound (BUS) imaging is a routine tool for diagnosis of liver cancers, while contrast-enhanced ultrasound (CEUS) provides additional inform...

Learn Fine-Grained Adaptive Loss for Multiple Anatomical Landmark Detection in Medical Images.

Automatic and accurate detection of anatomical landmarks is an essential operation in medical image analysis with a multitude of applications. Recent ...

A Deep Learning Localization Method for Measuring Abdominal Muscle Dimensions in Ultrasound Images.

Health professionals extensively use Two-Dimensional (2D) Ultrasound (US) videos and images to visualize and measure internal organs for various purpo...

Breast nodule classification with two-dimensional ultrasound using Mask-RCNN ensemble aggregation.

PURPOSE: The purpose of this study was to create a deep learning algorithm to infer the benign or malignant nature of breast nodules using two-dimensi...

Generating Synthetic Labeled Data From Existing Anatomical Models: An Example With Echocardiography Segmentation.

Deep learning can bring time savings and increased reproducibility to medical image analysis. However, acquiring training data is challenging due to t...

IFSS-Net: Interactive Few-Shot Siamese Network for Faster Muscle Segmentation and Propagation in Volumetric Ultrasound.

We present an accurate, fast and efficient method for segmentation and muscle mask propagation in 3D freehand ultrasound data, towards accurate volume...

Silver Nanoparticles as an Effective Antimicrobial against Otitis Media Pathogens.

Otitis Media (OM) is the most common reason for U.S. children to receive prescribed oral antibiotics, leading to potential to cause antibiotic resista...

Artificial intelligence system reduces false-positive findings in the interpretation of breast ultrasound exams.

Though consistently shown to detect mammographically occult cancers, breast ultrasound has been noted to have high false-positive rates. In this work,...

A new phase transfer nanocatalyst NiFeO-PEG for removal of dibenzothiophene by an ultrasound assisted oxidative process: kinetics, thermodynamic study and experimental design.

In this study, NiFeO-PEG, an effective nanocatalyst was synthesized a hydrothermal method using different PEG concentrations and synthesis times. The...

Towards Scale and Position Invariant Task Classification using Normalised Visual Scanpaths in Clinical Fetal Ultrasound.

We present a method for classifying tasks in fetal ultrasound scans using the eye-tracking data of sonographers. The visual attention of a sonographer...

Magneto-Responsive Microneedle Robots for Intestinal Macromolecule Delivery.

Oral administration is the most convenient and commonly used approach for drug delivery, while it is still a challenge to overcome the complicated gas...

Ultrasound Image Features under Deep Learning in Breast Conservation Surgery for Breast Cancer.

This study was to analyze the effect of the combined application of deep learning technology and ultrasound imaging on the effect of breast-conserving...

A category attention instance segmentation network for four cardiac chambers segmentation in fetal echocardiography.

Fetal echocardiography is an essential and comprehensive examination technique for the detection of fetal heart anomalies. Accurate cardiac chambers s...