Latest AI and machine learning research in pregnancy for healthcare professionals.
OBJECTIVE: Segmentation of anatomical structures in ultrasound images requires vast radiological knowledge and experience. Moreover, the manual segmentation often results in subjective variations, therefore, an automatic segmentation is desirable. We aim to develop a fully convolutional neural network (FCNN) with attentional deep supervision for the automatic and accurate segmentation of the ultra...
OBJECTIVE: Obstetricians mainly use ultrasound imaging for fetal biometric measurements. However, such measurements are cumbersome. Hence, there is urgent need for automatic biometric estimation. Automated analysis of ultrasound images is complicated owing to the patient-specific, operator-dependent, and machine-specific characteristics of such images.
PURPOSE: Early diagnosis of triple-negative (TN) breast cancer is important due to its aggressive biological characteristics, poor clinical outcomes, ...
The field of nanomedicine has made substantial strides in the areas of therapeutic and diagnostic development. For example, nanoparticle-modified drug...
OBJECTIVE: To describe a novel ultrasound-guided posterior extraconal block in the dog.
The manuscript describes an ultrasound image segmentation technique based on the fractional Brownian motion (FBM) model. Here, the ultrasound images a...
Hepatic impairment is common during hyperthyroidism. It is most often asymptomatic. Hyperthyroidism revealed by jaundice has been rarely described in ...
Despite the progress in the area of food safety, foodborne diseases still represent a massive challenge to the public health systems worldwide, mainly...
We present a novel multi-task convolutional neural network called Multi-task SonoEyeNet () that learns to generate clinically relevant visual attentio...
Accurate localization of structural abnormalities is a precursor for image-based prenatal assessment of adverse conditions. For clinical screening and...
We propose a framework for localization and classification of masses in breast ultrasound images. We have experimentally found that training convoluti...
The thyroid is one of the largest endocrine glands in the human body, which is involved in several body mechanisms like controlling protein synthesis ...
Ultrasound is one of emerging technique's which is being investigated extremely on food applications and extraction process. In this study, ultrasound...
OBJECTIVE: To evaluate the optimum percent on time for the most efficient lens fragment removal using long-pulse torsional ultrasound (US).
BACKGROUND: Fulfilling the vision of Semantic Web requires an accurate data model for organizing knowledge and sharing common understanding of the dom...
PURPOSE: To evaluate the feasibility and reproducibility of artificial intelligence software (Smartplanes) to automatically identify the transthalamic...
INTRODUCTION: Local anaesthetic (LA) with highly selective alpha-2 agonist dexmedetomidine has not been evaluated in adductor canal block (ACB) for ar...
With an aim to increase the capture range and accelerate the performance of state-of-the-art inter-subject and subject-to-template 3-D rigid registrat...
BACKGROUND: While there is increasing interest in identifying pregnancies at risk for adverse outcome, existing prediction models have not adequately ...
Osteosarcoma is an aggressive form of bone cancer mostly affecting young people. To date, the most effective strategy for the treatment of osteosarcom...