Pregnancy

Rethinking Breast Cancer Diagnosis through Deep Learning Based Image Recognition.

This paper explored techniques for diagnosing breast cancer using deep learning based medical image recognition. X-ray (Mammography) images, ultrasound images, and histopathology images are used to improve the accuracy of the process by diagnosing breast cancer classification and by inferring their affected location. For this goal, the image recognition application strategies for the maximal diagn...

Ultrasound Volume Reconstruction From Freehand Scans Without Tracking.

Transrectal ultrasound is commonly used for guiding prostate cancer biopsy, where 3D ultrasound volume reconstruction is often desired. Current methods for 3D reconstruction from freehand ultrasound scans require external tracking devices to provide spatial information of an ultrasound transducer. This paper presents a novel deep learning approach for sensorless ultrasound volume reconstruction, w...

LN-Net: Perfusion Pattern-Guided Deep Learning for Lymph Node Metastasis Diagnosis Based on Contrast-Enhanced Ultrasound Videos.

OBJECTIVE: The blood flow in lymph nodes reflects important pathological features. However, most intelligent diagnosis based on contrast-enhanced ultr...

Artificial intelligence and fetal ultrasound biometry: Challenges and perspectives.

Generalisability of fetal ultrasound deep learning models to low-resource imaging settings in five African countries.

Most artificial intelligence (AI) research and innovations have concentrated in high-income countries, where imaging data, IT infrastructures and clin...

APLUS: A Python library for usefulness simulations of machine learning models in healthcare.

Despite the creation of thousands of machine learning (ML) models, the promise of improving patient care with ML remains largely unrealized. Adoption ...

Development and testing of a multi-lingual Natural Language Processing-based deep learning system in 10 languages for COVID-19 pandemic crisis: A multi-center study.

PURPOSE: The COVID-19 pandemic has drastically disrupted global healthcare systems. With the higher demand for healthcare and misinformation related t...

HCTNet: A hybrid CNN-transformer network for breast ultrasound image segmentation.

Automatic breast ultrasound image segmentation helps radiologists to improve the accuracy of breast cancer diagnosis. In recent years, the convolution...

Recent Advances in the Applications of Additive Manufacturing (3D Printing) in Drug Delivery: A Comprehensive Review.

There has been a tremendous increase in the investigations of three-dimensional (3D) printing for biomedical and pharmaceutical applications, and drug...

Medical microrobots in reproductive medicine from the bench to the clinic.

Medical microrobotics is an emerging field that aims at non-invasive diagnosis and therapy inside the human body through miniaturized sensors and actu...

Multi-centre deep learning for placenta segmentation in obstetric ultrasound with multi-observer and cross-country generalization.

The placenta is crucial to fetal well-being and it plays a significant role in the pathogenesis of hypertensive pregnancy disorders. Moreover, a timel...

Spatiotemporal analysis of speckle dynamics to track invisible needle in ultrasound sequences using convolutional neural networks: a phantom study.

PURPOSE: Accurate needle placement into the target point is critical for ultrasound interventions like biopsies and epidural injections. However, alig...

Biphasic burst and sustained transdermal delivery in vivo using an AI-optimized 3D-printed MN patch.

The objective of the present study was to fabricate microneedles for delivering lipophilic active ingredients (APIs) using digital light processing (D...

Strategy for automatic ultrasound (US) probe positioning in robot-assisted ultrasound guided radiation therapy.

. As part of image-guided radiotherapy, ultrasound-guided radiotherapy is currently already in use and under investigation for robot assisted systems ...

Sensing and Automation Technologies for Ornamental Nursery Crop Production: Current Status and Future Prospects.

The ornamental crop industry is an important contributor to the economy in the United States. The industry has been facing challenges due to continuou...

A deep learning model with data integration of ultrasound contrast-enhanced micro-flow cines, B-mode images, and clinical parameters for diagnosing significant liver fibrosis in patients with chronic hepatitis B.

OBJECTIVE: To develop and investigate a deep learning model with data integration of ultrasound contrast-enhanced micro-flow (CEMF) cines, B-mode imag...

Design and evaluation of vascular interventional robot system for complex coronary artery lesions.

At present, most vascular intervention robots cannot cope with the more common coronary complex lesions in the clinic. Moreover, the lack of effective...

Simulation-to-real generalization for deep-learning-based refraction-corrected ultrasound tomography image reconstruction.

. The image reconstruction of ultrasound computed tomography is computationally expensive with conventional iterative methods. The fully learned direc...

Investigation of optimal convolutional neural network conditions for thyroid ultrasound image analysis.

Neural network models have been used to analyze thyroid ultrasound (US) images and stratify malignancy risk of the thyroid nodules. We investigated th...

Prospective Real-Time Validation of a Lung Ultrasound Deep Learning Model in the ICU.

OBJECTIVES: To evaluate the accuracy of a bedside, real-time deployment of a deep learning (DL) model capable of distinguishing between normal (A line...