AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Models, Anatomic

Showing 31 to 40 of 67 articles

Clear Filters

Simplifying models and estimating grasp performance for comparing dynamic hand orthosis concepts.

PloS one
While designing a dynamic hand orthosis to assist during activities of daily living, the designer has to know whether a concept will have sufficient grasp performance to support these activities. This is often estimated by measuring the interaction f...

Zebrafish Embryo Vessel Segmentation Using a Novel Dual ResUNet Model.

Computational intelligence and neuroscience
Zebrafish embryo fluorescent vessel analysis, which aims to automatically investigate the pathogenesis of diseases, has attracted much attention in medical imaging. Zebrafish vessel segmentation is a fairly challenging task, which requires distinguis...

Application of convolutional neural networks for classification of adult mosquitoes in the field.

PloS one
Dengue, chikungunya and Zika are arboviruses transmitted by mosquitos of the genus Aedes and have caused several outbreaks in world over the past ten years. Morphological identification of mosquitos is currently restricted due to the small number of ...

Sensor-based machine learning for workflow detection and as key to detect expert level in laparoscopic suturing and knot-tying.

Surgical endoscopy
INTRODUCTION: The most common way of assessing surgical performance is by expert raters to view a surgical task and rate a trainee's performance. However, there is huge potential for automated skill assessment and workflow analysis using modern techn...

Enabling machine learning in X-ray-based procedures via realistic simulation of image formation.

International journal of computer assisted radiology and surgery
PURPOSE: Machine learning-based approaches now outperform competing methods in most disciplines relevant to diagnostic radiology. Image-guided procedures, however, have not yet benefited substantially from the advent of deep learning, in particular b...

Automatic annotation of surgical activities using virtual reality environments.

International journal of computer assisted radiology and surgery
PURPOSE: Annotation of surgical activities becomes increasingly important for many recent applications such as surgical workflow analysis, surgical situation awareness, and the design of the operating room of the future, especially to train machine l...

Novel evaluation of surgical activity recognition models using task-based efficiency metrics.

International journal of computer assisted radiology and surgery
PURPOSE: Surgical task-based metrics (rather than entire procedure metrics) can be used to improve surgeon training and, ultimately, patient care through focused training interventions. Machine learning models to automatically recognize individual ta...

Interfacing Soft and Hard: A Spring Reinforced Actuator.

Soft robotics
Muscular hydrostats have long been a source of inspiration for soft robotic designs. With their inherent compliance, they excel in unpredictable environments and can gently manipulate objects with ease. However, their performance lacks where high for...

Computational modeling of the effects of EEG volume conduction on functional connectivity metrics. Application to Alzheimer's disease continuum.

Journal of neural engineering
OBJECTIVE: The aim of this study was to evaluate the effect of electroencephalographic (EEG) volume conduction in different measures of functional connectivity and to characterize the EEG coupling alterations at the different stages of dementia due t...

Incorporating prior shape knowledge via data-driven loss model to improve 3D liver segmentation in deep CNNs.

International journal of computer assisted radiology and surgery
PURPOSE: Convolutional neural networks (CNNs) have obtained enormous success in liver segmentation. However, there are several challenges, including low-contrast images, and large variations in the shape, and appearance of the liver. Incorporating pr...