AI Medical Compendium Topic

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Fetus

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Brain views that benefit from three-dimensional ultrasound.

Current opinion in obstetrics & gynecology
PURPOSE OF REVIEW: Fetal central nervous system malformations are among the most common congenital anomalies. Whereas simple axial views are sufficient for basic fetal brain examination, other important views are essential for a more detailed examina...

Automatic quality assessment for 2D fetal sonographic standard plane based on multitask learning.

Medicine
The quality control of fetal sonographic (FS) images is essential for the correct biometric measurements and fetal anomaly diagnosis. However, quality control requires professional sonographers to perform and is often labor-intensive. To solve this p...

Single-cell analyses and machine learning define hematopoietic progenitor and HSC-like cells derived from human PSCs.

Blood
Hematopoietic stem and progenitor cells (HSPCs) develop in distinct waves at various anatomical sites during embryonic development. The in vitro differentiation of human pluripotent stem cells (hPSCs) recapitulates some of these processes; however, i...

Using deep-learning algorithms to classify fetal brain ultrasound images as normal or abnormal.

Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology
OBJECTIVES: To evaluate the feasibility of using deep-learning algorithms to classify as normal or abnormal sonographic images of the fetal brain obtained in standard axial planes.

Fusing autonomy and sociality via embodied emergence and development of behaviour and cognition from fetal period.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences
Human-centred AI/Robotics are quickly becoming important. Their core claim is that AI systems or robots must be designed and work for the benefits of humans with no harm or uneasiness. It essentially requires the realization of autonomy, sociality an...

A Crossover Comparison of Standard and Telerobotic Approaches to Prenatal Sonography.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVES: To determine the feasibility of a telerobotic approach to remotely perform prenatal sonographic examinations.

Fetal MRI Synthesis via Balanced Auto-Encoder Based Generative Adversarial Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Machine learning approaches for image analysis require large amounts of training imaging data. As an alternative, the use of realistic synthetic data reduces the high cost associated to medical image acquisition, as well as avoiding confidentiality a...

Interactive Medical Image Segmentation Using Deep Learning With Image-Specific Fine Tuning.

IEEE transactions on medical imaging
Convolutional neural networks (CNNs) have achieved state-of-the-art performance for automatic medical image segmentation. However, they have not demonstrated sufficiently accurate and robust results for clinical use. In addition, they are limited by ...

A Deep Convolutional Neural Network-Based Framework for Automatic Fetal Facial Standard Plane Recognition.

IEEE journal of biomedical and health informatics
Ultrasound imaging has become a prevalent examination method in prenatal diagnosis. Accurate acquisition of fetal facial standard plane (FFSP) is the most important precondition for subsequent diagnosis and measurement. In the past few years, conside...

A deep learning approach for fetal QRS complex detection.

Physiological measurement
OBJECTIVE: Non-invasive foetal electrocardiography (NI-FECG) has the potential to provide more additional clinical information for detecting and diagnosing fetal diseases. We propose and demonstrate a deep learning approach for fetal QRS complex dete...