Pregnancy

Deep learning-based digitization of prostate brachytherapy needles in ultrasound images.

PURPOSE: To develop, and evaluate the performance of, a deep learning-based three-dimensional (3D) convolutional neural network (CNN) artificial intelligence (AI) algorithm aimed at finding needles in ultrasound images used in prostate brachytherapy.

Thrombolysis of Pulmonary Emboli via Endobronchial Ultrasound-Guided Transbronchial Needle Injection.

BACKGROUND: Endobronchial ultrasound-guided transbronchial needle injection (EBUS-TBNI) is a novel technique for treating peribronchial targets. The aim of this study was to evaluate preliminary feasibility of thrombolysis of pulmonary emboli via EBUS-TBNI.

Prediction of obstetrical and fetal complications using automated electronic health record data.

An increasing number of delivering women experience major morbidity and mortality. Limited work has been done on automated predictive models that coul...

Tumor segmentation in automated whole breast ultrasound using bidirectional LSTM neural network and attention mechanism.

Accurate breast mass segmentation of automated breast ultrasound (ABUS) is a great help to breast cancer diagnosis and treatment. However, the lack of...

Telerobotic ultrasound to provide obstetrical ultrasound services remotely during the COVID-19 pandemic.

INTRODUCTION: Obstetrical ultrasound imaging is critical in identifying at-risk pregnancies and informing clinical management. The coronavirus disease...

Breast ultrasound lesion classification based on image decomposition and transfer learning.

PURPOSE: In medical image analysis, deep learning has great application potential. Discovering a method for extracting valuable information from medic...

Plant Leaf Position Estimation with Computer Vision.

Autonomous analysis of plants, such as for phenotyping and health monitoring etc., often requires the reliable identification and localization of sing...

A multiple-channel and atrous convolution network for ultrasound image segmentation.

PURPOSE: Ultrasound image segmentation is a challenging task due to a low signal-to-noise ratio and poor image quality. Although several approaches ba...

Magnetic resonance imaging-ultrasound fusion-targeted biopsy combined with systematic 12-core ultrasound-guided biopsy improves the detection of clinically significant prostate cancer: Are we ready to abandon the systematic approach?

BACKGROUND: Multiparametric (mp) magnetic resonance imaging (MRI)-ultrasound fusion-targeted biopsy (TB) has improved the detection of clinically sign...

Telerobotic Sonography for Remote Diagnostic Imaging: Narrative Review of Current Developments and Clinical Applications.

Access to sonographers and sonologists is limited in many communities around the world. Telerobotic sonography (robotic ultrasound) is a new technolog...

Automatic multi-needle localization in ultrasound images using large margin mask RCNN for ultrasound-guided prostate brachytherapy.

Multi-needle localization in ultrasound (US) images is a crucial step of treatment planning for US-guided prostate brachytherapy. However, current com...

A machine learning algorithm supports ultrasound-naïve novices in the acquisition of diagnostic echocardiography loops and provides accurate estimation of LVEF.

Left ventricular ejection fraction (LVEF) is the most important parameter in the assessment of cardiac function. A machine-learning algorithm was trai...

Efficient and Robust Instrument Segmentation in 3D Ultrasound Using Patch-of-Interest-FuseNet with Hybrid Loss.

Instrument segmentation plays a vital role in 3D ultrasound (US) guided cardiac intervention. Efficient and accurate segmentation during the operation...

Estimating 3-dimensional liver motion using deep learning and 2-dimensional ultrasound images.

PURPOSE: The main purpose of this study is to construct a system to track the tumor position during radiofrequency ablation (RFA) treatment. Existing ...

Integration of AI and Machine Learning in Radiotherapy QA.

The use of machine learning and other sophisticated models to aid in prediction and decision making has become widely popular across a breadth of disc...

REDBot: Natural language process methods for clinical copy number variation reporting in prenatal and products of conception diagnosis.

BACKGROUND: Current copy number variation (CNV) identification methods have rapidly become mature. However, the postdetection processes such as varian...

Point-of-Care Ultrasound.

PURPOSE OF THE REVIEW: Point-of-care ultrasound using small ultrasound devices has expanded beyond emergency and critical care medicine to many other ...

An Innovative Artificial Intelligence-Based App for the Diagnosis of Gestational Diabetes Mellitus (GDM-AI): Development Study.

BACKGROUND: Gestational diabetes mellitus (GDM) can cause adverse consequences to both mothers and their newborns. However, pregnant women living in l...

A multi-task, multi-stage deep transfer learning model for early prediction of neurodevelopment in very preterm infants.

Survivors following very premature birth (i.e., ≤ 32 weeks gestational age) remain at high risk for neurodevelopmental impairments. Recent advances in...

Machine Learning-Based DNA Methylation Score for Fetal Exposure to Maternal Smoking: Development and Validation in Samples Collected from Adolescents and Adults.

BACKGROUND: Fetal exposure to maternal smoking during pregnancy is associated with the development of noncommunicable diseases in the offspring. Mater...