Pregnancy

Contrastive rendering with semi-supervised learning for ovary and follicle segmentation from 3D ultrasound.

Segmentation of ovary and follicles from 3D ultrasound (US) is the crucial technique of measurement tools for female infertility diagnosis. Since manual segmentation is time-consuming and operator-dependent, an accurate and fast segmentation method is highly demanded. However, it is challenging for current deep-learning based methods to segment ovary and follicles precisely due to ambiguous bounda...

External validation of machine learning models including newborn metabolomic markers for postnatal gestational age estimation in East and South-East Asian infants.

 Postnatal gestational age (GA) algorithms derived from newborn metabolic profiles have emerged as a novel method of acquiring population-level preterm birth estimates in low resource settings. To date, model development and validation have been carried out in North American settings. Validation outside of these settings is warranted.    This was a retrospective database study using data from newb...

Machine learning-based analysis of operator pupillary response to assess cognitive workload in clinical ultrasound imaging.

INTRODUCTION: Pupillometry, the measurement of eye pupil diameter, is a well-established and objective modality correlated with cognitive workload. In...

Advanced deep learning methodology for accurate, real-time segmentation of high-resolution intravascular ultrasound images.

AIMS: The aim of this study is to develop and validate a deep learning (DL) methodology capable of automated and accurate segmentation of intravascula...

Deep Learning Pitfall: Impact of Novel Ultrasound Equipment Introduction on Algorithm Performance and the Realities of Domain Adaptation.

OBJECTIVES: To test deep learning (DL) algorithm performance repercussions by introducing novel ultrasound equipment into a clinical setting.

Capsule networks for segmentation of small intravascular ultrasound image datasets.

PURPOSE: Intravascular ultrasound (IVUS) imaging is crucial for planning and performing percutaneous coronary interventions. Automatic segmentation of...

Cisplatin and paclitaxel co-delivery nanosystem for ovarian cancer chemotherapy.

We have designed and developed an effective drug delivery system using biocompatible polymer of poly (ethylene glycol)-polyaspartic acid (mPEG-PAsp) f...

Cyclic arginine-glycine-aspartic acid-modified red blood cells for drug delivery: Synthesis and evaluation.

Red blood cells (RBCs) are an excellent choice for cell preparation research because of their biocompatibility, high drug loading, and long half-life....

In Vitro Assessment for Dose Preparation and Simulated Administration of Azithromycin Suspensions via Enteral Feeding Tubes.

Administration of medication via enteral feeding tubes (EFT) is common in cases where patients are unable to swallow the dosage form or a patient is i...

Preliminary examination of the potential of robot-assisted sonography - An ergonomic tool for obstetric sonographers.

The aim of this study was to explore the ergonomic challenges, the needs and reservations related to robot-assisted ultrasound for obstetric sonograph...

Liver disease classification from ultrasound using multi-scale CNN.

PURPOSE: Ultrasound (US) is the preferred modality for fatty liver disease diagnosis due to its noninvasive, real-time, and cost-effective imaging cap...

Reliable Prediction Models Based on Enriched Data for Identifying the Mode of Childbirth by Using Machine Learning Methods: Development Study.

BACKGROUND: The use of artificial intelligence has revolutionized every area of life such as business and trade, social and electronic media, educatio...

Hybridized neural networks for non-invasive and continuous mortality risk assessment in neonates.

Premature birth is the primary risk factor in neonatal deaths, with the majority of extremely premature babies cared for in neonatal intensive care un...

Multi-Parametric Fusion of 3D Power Doppler Ultrasound for Fetal Kidney Segmentation Using Fully Convolutional Neural Networks.

Kidney development is key to the long-term health of the fetus. Renal volume and vascularity assessed by 3D ultrasound (3D-US) are known markers of we...

Recognition of Thyroid Ultrasound Standard Plane Images Based on Residual Network.

Ultrasound is one of the critical methods for diagnosis and treatment in thyroid examination. In clinical application, many reasons, such as large out...

Searching collaborative agents for multi-plane localization in 3D ultrasound.

3D ultrasound (US) has become prevalent due to its rich spatial and diagnostic information not contained in 2D US. Moreover, 3D US can contain multipl...

Joint Detection of Tap and CEA Based on Deep Learning Medical Image Segmentation: Risk Prediction of Thyroid Cancer.

In recent years, the incidence of thyroid nodules has shown an increasing trend year by year and has become one of the important diseases that endange...

Automatic Hyoid Bone Tracking in Real-Time Ultrasound Swallowing Videos Using Deep Learning Based and Correlation Filter Based Trackers.

(1) Background: Ultrasound provides a radiation-free and portable method for assessing swallowing. Hyoid bone locations and displacements are often us...

Variational Formulation of Unsupervised Deep Learning for Ultrasound Image Artifact Removal.

Recently, deep learning approaches have been successfully used for ultrasound (US) image artifact removal. However, paired high-quality images for sup...

Mini-COVIDNet: Efficient Lightweight Deep Neural Network for Ultrasound Based Point-of-Care Detection of COVID-19.

Lung ultrasound (US) imaging has the potential to be an effective point-of-care test for detection of COVID-19, due to its ease of operation with mini...