Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Behavior of Concrete Under Compressive Load

Behavior of Concrete Under Compressive Load

Concrete exhibits specific behaviors under different compressive loads. Understanding this is crucial for understanding its structural integrity. When concrete undergoes uniaxial compression, it tends to develop cracks that run parallel to the direction of the force. These parallel cracks stem from localized tensile stresses that occur perpendicular to the compression direction. Additionally, angled cracks may appear due to the formation of shear planes.
As the concrete specimen fractures under...

Avoidance Learning and Learned Helplessness

Avoidance Learning and Learned Helplessness

Avoidance learning and learned helplessness are critical concepts in understanding behavioral responses to negative stimuli.
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

Associative Learning

Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...

Purposive Learning

Purposive Learning

E. C. Tolman emphasized the purposiveness of behavior — the idea that much of our behavior is goal-directed. For instance, employees who aim for a promotion work diligently to meet their targets. Tolman argued that when classical conditioning and operant conditioning occur, the organism acquires certain expectations. In classical conditioning, a child might fear a dog because they expect it to bite. In operant conditioning, a person might consistently work overtime because they expect a...

Observational Learning

Observational Learning

Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...

Learning Disabilities

Learning Disabilities

Learning disabilities are cognitive disorders caused by neurological impairments that affect cognitive functions like language and reading, without indicating overall intellectual or developmental challenges. These disabilities differ from global intellectual or developmental disabilities as they are limited to distinct cognitive functions. Common learning disabilities include dysgraphia, dyslexia, and dyscalculia, each of which impacts unique aspects of learning.
Dyslexia
Dyslexia is a...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

MicroKAN: Mapping human brain microstructure using diffusion MRI and adaptive nonlinear modeling.

NeuroImage·2026

Same author

I2I-Mamba: Multi-modal medical image synthesis via selective state space modeling.

IEEE transactions on bio-medical engineering·2026

Same author

Meta-Entity Driven Triplet Mining for Aligning Medical Vision-Language Models.

IEEE journal of biomedical and health informatics·2026

Same author

Semi-supervision for clinical contrast-weighted image synthesis from magnetic resonance fingerprinting.

Magma (New York, N.Y.)·2026

Same author

Learning Fourier-Constrained Diffusion Bridges for MRI Reconstruction.

IEEE transactions on medical imaging·2026

Same author

Editorial AI Reviewer (AIR) Trial for Responsible, Secure, and Efficient Peer Review.

IEEE transactions on medical imaging·2026

Search research articles

Related Experiment Video

Updated: Feb 9, 2026

Measurement of the Compressibility of Cell and Nucleus Based on Acoustofluidic Microdevice

Measurement of the Compressibility of Cell and Nucleus Based on Acoustofluidic Microdevice

Published on: July 14, 2022

Learning-Based Compressive MRI.

Baran Gozcu, Rabeeh Karimi Mahabadi, Yen-Huan Li

IEEE Transactions on Medical Imaging

|June 6, 2018

Summary

This summary is machine-generated.

This study introduces a new learning-based framework to optimize magnetic resonance imaging (MRI) sampling patterns for specific reconstruction methods and anatomy. This approach improves MRI data acquisition by considering both noiseless and noisy conditions.

More Related Videos

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

A MRI-Based Toolbox for Neurosurgical Planning in Nonhuman Primates

A MRI-Based Toolbox for Neurosurgical Planning in Nonhuman Primates

Published on: July 17, 2020

Related Experiment Videos

Last Updated: Feb 9, 2026

Measurement of the Compressibility of Cell and Nucleus Based on Acoustofluidic Microdevice

Measurement of the Compressibility of Cell and Nucleus Based on Acoustofluidic Microdevice

Published on: July 14, 2022

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

A MRI-Based Toolbox for Neurosurgical Planning in Nonhuman Primates

A MRI-Based Toolbox for Neurosurgical Planning in Nonhuman Primates

Published on: July 17, 2020

Area of Science:

Medical Imaging
Machine Learning
Signal Processing

Background:

Magnetic Resonance Imaging (MRI) utilizes non-linear reconstruction algorithms with Fourier subsampling patterns.
Current subsampling pattern design is often isolated from reconstruction rules and specific anatomical considerations.

Purpose of the Study:

To develop a learning-based framework for optimizing MRI subsampling patterns.
To tailor sampling patterns to specific reconstruction algorithms and anatomical targets.
To address both noiseless and noisy data acquisition scenarios.

Main Methods:

A learning algorithm utilizing representative training signals to search for optimal sampling patterns.
Introduction of a novel parameter-free greedy mask selection method.
Validation across diverse reconstruction rules and performance metrics.

Main Results:

The proposed framework effectively optimizes MRI subsampling patterns.
The greedy mask selection method demonstrates broad applicability and effectiveness.
Numerical findings are rigorously supported by statistical learning theory.

Conclusions:

The developed framework offers a principled approach to designing MRI sampling strategies.
This method enhances MRI reconstruction performance by integrating pattern design with reconstruction and anatomy.
The framework provides a robust and theoretically justified solution for adaptive MRI data acquisition.