Related Experiment Video
Updated: Feb 9, 2026

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
Published on: November 30, 2022
Real-Time Medical Video Denoising with Deep Learning: Application to Angiography
1Yale University, School of Medicine, Cedar St, New Haven, CT, USA.
Abstract:
This paper describes the design, training, and evaluation of a deep neural network for removing noise from medical fluoroscopy videos. The method described in this work, unlike the current standard techniques for video denoising, is able to deliver a result quickly enough to be used in real-time scenarios. Furthermore, this method is able to produce results of a similar quality to the existing industry-standard denoising techniques.
More Related Videos
Related Concept Videos
Real-World Application of Classical Conditioning
Higher-order, or second-order, conditioning occurs when a neutral stimulus becomes associated with an already established conditioned stimulus through repeated pairings. For instance, if a dog has been...
Real Time RT-PCR
The real-time quantification of the number of amplified products is...
Inhaled Medications
Avoidance Learning and Learned Helplessness
Avoidance learning occurs when an organism learns that a specific behavior can prevent an unpleasant outcome. For example, a student who receives a bad grade may start studying harder to avoid future poor grades. This behavior persists even when the negative outcome is no longer present. Avoidance learning is powerful because it maintains behavior in the absence of the...
Associative Learning
Classical conditioning, also known...
Purposive Learning

