Pregnancy

Attention-based Fusion Network for Breast Cancer Segmentation and Classification Using Multi-modal Ultrasound Images.

OBJECTIVE: Breast cancer is one of the most commonly occurring cancers in women. Thus, early detection and treatment of cancer lead to a better outcome for the patient. Ultrasound (US) imaging plays a crucial role in the early detection of breast cancer, providing a cost-effective, convenient, and safe diagnostic approach. To date, much research has been conducted to facilitate reliable and effect...

Effect of the Ultrasound-Guided Interscalene and Supraclavicular Blocks on the C4 Dermatome.

PURPOSE: The C4 dermatome anesthesia holds significance for arthroscopic shoulder surgery. However, the reliability of achieving C4 dermatome anesthesia with the current low-dose ultrasound-guided interscalene block (ISB) and supraclavicular block (SCB) remains uncertain. This prospective, single-center study examined the effects of ultrasound-guided interscalene block (ISB) and supraclavicular bl...

Spontaneous Hepatic Rupture Complicating Preeclampsia and HELLP Syndrome: A Case Report.

Spontaneous hepatic rupture is a rare complication that occurs in pregnant mothers with HELLP syndrome, or preeclampsia with severe features, or ecla...

Pixels to precision: Neuroradiology's leap into 3D printing for personalized medicine.

The realm of precision medicine, particularly its application within various sectors, shines notably in neuroradiology, where it leverages the advance...

Strategies for the design of biomimetic cell-penetrating peptides using AI-driven in silico tools for drug delivery.

Cell-penetrating peptides (CPP) have gained rapid attention over the last 25 years; this is attributed to their versatility, customisation, and 'Troja...

Automatic Segmentation of Sylvian Fissure in Brain Ultrasound Images of Pre-Term Infants Using Deep Learning Models.

OBJECTIVE: Segmentation of brain sulci in pre-term infants is crucial for monitoring their development. While magnetic resonance imaging has been used...

Deep learning for segmentation of colorectal carcinomas on endoscopic ultrasound.

BACKGROUND: Bowel-preserving local resection of early rectal cancer is less successful if the tumor infiltrates the muscularis propria as opposed to s...

Functional MRGPRX2 expression on peripheral blood-derived human mast cells increases at low seeding density and is suppressed by interleukin-9 and fetal bovine serum.

Primary human mast cells (MC) obtained through culturing of blood-derived MC progenitors are the preferred model for the study of MRGPRX2- IgE-media...

WFUMB Commentary Paper on Artificial intelligence in Medical Ultrasound Imaging.

Artificial intelligence (AI) is defined as the theory and development of computer systems able to perform tasks normally associated with human intelli...

3D electron microscopy for analyzing nanoparticles in the tumor endothelium.

Delivering medical agents to diseased tissues has been challenging, leading researchers to study the in vivo transport process in the body for improvi...

CNN-Based Cross-Modality Fusion for Enhanced Breast Cancer Detection Using Mammography and Ultrasound.

Breast cancer is a leading cause of mortality among women in Taiwan and globally. Non-invasive imaging methods, such as mammography and ultrasound, a...

Imaging-guided bioresorbable acoustic hydrogel microrobots.

Micro- and nanorobots excel in navigating the intricate and often inaccessible areas of the human body, offering immense potential for applications su...

Performance of automated machine learning in detecting fundus diseases based on ophthalmologic B-scan ultrasound images.

AIM: To evaluate the efficacy of automated machine learning (AutoML) models in detecting fundus diseases using ocular B-scan ultrasound images.

BUSClean: Open-source software for breast ultrasound image pre-processing and knowledge extraction for medical AI.

Development of artificial intelligence (AI) for medical imaging demands curation and cleaning of large-scale clinical datasets comprising hundreds of ...

A dual-decoder banded convolutional attention network for bone segmentation in ultrasound images.

BACKGROUND: Ultrasound (US) has great potential for application in computer-assisted orthopedic surgery (CAOS) due to its non-radiative, cost-effectiv...

Diagnostic modalities in the mediastinum and the role of bronchoscopy in mediastinal assessment: a narrative review.

BACKGROUND AND OBJECTIVE: Diagnosis of pathology in the mediastinum has proven quite challenging, given the wide variability of both benign and malign...

Deep-DM: Deep-Driven Deformable Model for 3D Image Segmentation Using Limited Data.

Objective - Medical image segmentation is essential for several clinical tasks, including diagnosis, surgical and treatment planning, and image-guided...

Predicting adverse pregnancy outcome in Rwanda using machine learning techniques.

BACKGROUND: Adverse pregnancy outcomes pose significant risk to maternal and neonatal health, contributing to morbidity, mortality, and long-term deve...

A multimodal machine learning model for the stratification of breast cancer risk.

Machine learning models for the diagnosis of breast cancer can facilitate the prediction of cancer risk and subsequent patient management among other ...

Training humans to supplement a machine learning system: The role of guides in a digital mental health intervention.

Machine learning (ML) is increasingly prevalent in mental health care, with contemporary initiatives leveraging these technologies, sometimes in combi...