Pregnancy

Artificial Intelligence Assisted Multi-modal Photoacoustic-Ultrasound Imaging for Studying Renal Tissue Function and Hemodynamics.

Combined functional-anatomic imaging modalities, which integrate the benefits of visualizing gross anatomy along with the functional or metabolic information of tissue has revolutionized the world of medical imaging. However, such existing imaging modalities are very costly. An alternative option could be a hybrid modality combining contrast-enhanced ultrasound, doppler and photoacoustic imaging. ...

A Comparative Study of Deep Learning Methods for Multi-Class Semantic Segmentation of 2D Kidney Ultrasound Images.

Ultrasound (US) imaging is a widely used medical imaging modality for the diagnosis, monitoring, and surgical planning for kidney conditions. Thus, accurate segmentation of the kidney and internal structures in US images is essential for the assessment of kidney function and the detection of pathological conditions, such as cysts, tumors, and kidney stones. Therefore, there is a need for automated...

Single Image based Super Resolution Ultrasound Imaging Using Residual Learning of Wavelet Features.

The generation of super resolution ultrasound images from the low-resolution (LR) brightness mode (B-mode) images acquired by the portable point of ca...

Fetal Re-Identification in Multiple Pregnancy Ultrasound Images Using Deep Learning.

Ultrasound examinations during pregnancy can detect abnormal fetal development, which is a leading cause of perinatal mortality. In multiple pregnanci...

The Effect of Fetal Heart Rate Segment Selection on Deep Learning Models for Fetal Compromise Detection.

Monitoring the fetal heart rate (FHR) is common practice in obstetric care to assess the risk of fetal compromise. Unfortunately, human interpretation...

Introduction to Point-of-Care Ultrasonography.

Medical ultrasonography was first used as a diagnostic tool in 1942 by Theodore Karl Dussik to visualize brain structures. Use of ultrasonography broa...

Towards an Explainable AI-Based Tool to Predict Preterm Birth.

Preterm birth (PTB) is defined as delivery occurring before 37 weeks of gestation. In this paper, Artificial Intelligence (AI)-based predictive models...

Development and Validation of a Radiomics Model Based on 3-Dimensional Endoanal Rectal Ultrasound of Rectal Cancer for Predicting Lymph Node Metastasis.

BACKGROUND: Development of a radiomics model for predicting lymph node metastasis status in rectal cancer patients based on 3-dimensional endoanal rec...

A hybrid artificial intelligence model leverages multi-centric clinical data to improve fetal heart rate pregnancy prediction across time-lapse systems.

STUDY QUESTION: Can artificial intelligence (AI) algorithms developed to assist embryologists in evaluating embryo morphokinetics be enriched with mul...

Digital health and technologies.

Digital health was given impetus by the COVID-19 pandemic and demonstrated its potential for the delivery of safe care in the community. Remote monito...

Machine learning-based evaluation of application value of pulse wave parameter model in the diagnosis of hypertensive disorder in pregnancy.

Hypertensive disorder in pregnancy (HDP) remains a major health burden, and it is associated with systemic cardiovascular adaptation. The pulse wave i...

[Fetal electrocardiogram signal extraction and analysis method combining fast independent component analysis algorithm and convolutional neural network].

Fetal electrocardiogram (ECG) signals provide important clinical information for early diagnosis and intervention of fetal abnormalities. In this pape...

Improving artificial intelligence pipeline for liver malignancy diagnosis using ultrasound images and video frames.

Recent developments of deep learning methods have demonstrated their feasibility in liver malignancy diagnosis using ultrasound (US) images. However, ...

Tracing human life trajectory using gut microbial communities by context-aware deep learning.

The gut microbial communities are highly plastic throughout life, and the human gut microbial communities show spatial-temporal dynamic patterns at di...

Enhancing Therapeutic Delivery Using Micro- and Nanorobots.

"The traditional way of delivering drugs has a very low efficiency. For instance, with solid tumors, drug delivery efficiency is reported to be lower ...

A novel method for conformity assessment testing of therapeutic ultrasounds for post-market surveillance purposes.

BACKGROUND: Therapeutic ultrasounds are medical devices used for treatment of conditions such muscle spasms, joint contractures or general muscle pain...

Machine learning analysis of breast ultrasound to classify triple negative and HER2+ breast cancer subtypes.

OBJECTIVES: Early diagnosis of triple-negative (TN) and human epidermal growth factor receptor 2 positive (HER2+) breast cancer is important due to it...

Prediction of Axillary Lymph Node Metastatic Load of Breast Cancer Based on Ultrasound Deep Learning Radiomics Nomogram.

Axillary lymph node (ALN) metastatic load is very important in the diagnosis and treatment of breast cancer (BC). We aimed to construct a model for p...

Clinical Importance of 3D Volography in Breast Imaging.

The clinical applications of the volography algorithm and concomitant refraction-corrected reflection algorithm as described in Chap. 10 are discussed...

3D Printable Drug Delivery Systems: Next-generation Healthcare Technology and Regulatory Aspects.

A revolutionary shift in healthcare has been sparked by the development of 3D printing, propelling us into an era replete with boundless opportunities...