Pregnancy

Deep learning radiomics based on contrast-enhanced ultrasound images for assisted diagnosis of pancreatic ductal adenocarcinoma and chronic pancreatitis.

BACKGROUND: Accurate and non-invasive diagnosis of pancreatic ductal adenocarcinoma (PDAC) and chronic pancreatitis (CP) can avoid unnecessary puncture and surgery. This study aimed to develop a deep learning radiomics (DLR) model based on contrast-enhanced ultrasound (CEUS) images to assist radiologists in identifying PDAC and CP.

A robotic magnetic resonance-guided high-intensity focused ultrasound platform for neonatal neurosurgery: Assessment of targeting accuracy and precision in a brain phantom.

BACKGROUND: Intraventricular hemorrhage (IVH) is one of the most serious neurovascular complications resulting from premature birth. It can result in clotting of blood within the ventricles, which causes a buildup of cerebrospinal fluid that can lead to posthemorrhagic ventricular dilation and posthemorrhagic hydrocephalus. Currently, there are no direct treatments for these blood clots as the sta...

Tomographic Ultrasound Imaging in the Diagnosis of Breast Tumors under the Guidance of Deep Learning Algorithms.

This study was aimed to discuss the feasibility of distinguishing benign and malignant breast tumors under the tomographic ultrasound imaging (TUI) of...

A novel convolutional neural network for kidney ultrasound images segmentation.

BACKGROUND AND OBJECTIVE: Ultrasound imaging has been widely used in the screening of kidney diseases. The localization and segmentation of the kidney...

The challenges facing deep learning-based catheter localization for ultrasound guided high-dose-rate prostate brachytherapy.

BACKGROUND: Automated catheter localization for ultrasound guided high-dose-rate prostate brachytherapy faces challenges relating to imaging noise and...

Clinical application of a 5G-based telerobotic ultrasound system for thyroid examination on a rural island: a prospective study.

PURPOSE: To evaluate the feasibility of a 5G-based telerobotic ultrasound (US) system for thyroid examination on a rural island.

Automated 3D Fetal Brain Segmentation Using an Optimized Deep Learning Approach.

BACKGROUND AND PURPOSE: MR imaging provides critical information about fetal brain growth and development. Currently, morphologic analysis primarily r...

Deep learning fetal ultrasound video model match human observers in biometric measurements.

This work investigates the use of deep convolutional neural networks (CNN) to automatically perform measurements of fetal body parts, including head c...

ISSMF: Integrated semantic and spatial information of multi-level features for automatic segmentation in prenatal ultrasound images.

As an effective way of routine prenatal diagnosis, ultrasound (US) imaging has been widely used recently. Biometrics obtained from the fetal segmentat...

High-Frequency Ultrasound Dataset for Deep Learning-Based Image Quality Assessment.

This study aims at high-frequency ultrasound image quality assessment for computer-aided diagnosis of skin. In recent decades, high-frequency ultrasou...

Deep learning of quantitative ultrasound multi-parametric images at pre-treatment to predict breast cancer response to chemotherapy.

In this study, a novel deep learning-based methodology was investigated to predict breast cancer response to neo-adjuvant chemotherapy (NAC) using the...

Framework for Integrating Equity Into Machine Learning Models: A Case Study.

Predictive analytic models leveraging machine learning methods increasingly have become vital to health care organizations hoping to improve clinical ...

CT2US: Cross-modal transfer learning for kidney segmentation in ultrasound images with synthesized data.

Accurate segmentation of kidney in ultrasound images is a vital procedure in clinical diagnosis and interventional operation. In recent years, deep le...

A Multi-Task Learning Framework for Automated Segmentation and Classification of Breast Tumors From Ultrasound Images.

Breast cancer is one of the most fatal diseases leading to the death of several women across the world. But early diagnosis of breast cancer can help ...

Comparison between Dexmedetomidine and Clonidine as an Adjuvant to Ropivacaine in Ultrasound-Guided Adductor Canal Block for Postoperative Analgesia in Total Knee Replacement: A Randomized Controlled Trial.

BACKGROUND: Total knee replacement (TKR) surgeries are associated with significant postoperative pain. Ultrasound-guided adductor canal block is assoc...

Comparative Study of Bupivacaine-Fentanyl versus Ropivacaine-Fentanyl for Epidural Analgesia in Labor.

BACKGROUND: Labor pain is one of the most intense pains that a woman experiences. Almost 60% of primiparous women described the pain of uterine contra...

Effects of age, gender, and hemisphere on cerebrovascular hemodynamics in children and young adults: Developmental scores and machine learning classifiers.

A constant blood supply to the brain is required for mental function. Research with Doppler ultrasonography has important clinical value and burgeonin...

SMU-Net: Saliency-Guided Morphology-Aware U-Net for Breast Lesion Segmentation in Ultrasound Image.

Deep learning methods, especially convolutional neural networks, have been successfully applied to lesion segmentation in breast ultrasound (BUS) imag...

Predicting Embryo Viability Based on Self-Supervised Alignment of Time-Lapse Videos.

With self-supervised learning, both labeled and unlabeled data can be used for representation learning and model pretraining. This is particularly rel...

Unsupervised deep learning based approach to temperature monitoring in focused ultrasound treatment.

Temperature monitoring in ultrasound (US) imaging is important for various medical treatments, such as high-intensity focused US (HIFU) therapy or hyp...