Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

The Sense of Self: Reflected Self-Appraisal and Social Comparison02:57

The Sense of Self: Reflected Self-Appraisal and Social Comparison

55.9K
According to Charles Cooley, we base our image on what we think other people see (Cooley 1902). We imagine how we must appear to others, then react to this speculation. We don certain clothes, prepare our hair in a particular manner, wear makeup, use cologne, and the like—all with the notion that our presentation of ourselves is going to affect how others perceive us. We expect a certain reaction, and, if lucky, we get the one we desire and feel good about it. But more than that, Cooley...
55.9K
The Nucleosome Core Particle02:10

The Nucleosome Core Particle

14.4K
Nucleosomes are the DNA-histone complex, where the DNA strand is wound around the histone core. The histone core is an octamer containing two copies of H2A, H2B, H3, and H4 histone proteins.
The paradox
Nucleosomes, paradoxically, perform two opposite functions simultaneously. On the one hand, their main responsibility is to protect the delicate DNA strands from physical damage and help achieve a higher compaction ratio. While on the other hand, they must allow polymerase enzymes to access DNA...
14.4K
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

1.5K
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
1.5K
Measurement: Standard Units03:38

Measurement: Standard Units

79.2K
Every measurement provides three kinds of information: the size or magnitude of the measurement (a number), a standard of comparison for the measurement (a unit), and an indication of the uncertainty of the measurement. While the number and unit are explicitly represented when a quantity is written, the uncertainty is an aspect of the errors in the measurement results.
79.2K
Standard Electrode Potentials03:02

Standard Electrode Potentials

50.1K
On comparing the reactivity of silver and lead, it is observed that the two ionic species, Ag+ (aq) and Pb2+ (aq), show a difference in their redox reactivity towards copper: the silver ion undergoes spontaneous reduction, while the lead ion does not. This relative redox activity can be easily quantified in electrochemical cells by a property called cell potential. This property is commonly known as cell voltage in electrochemistry, and it is a measure of the energy which accompanies the charge...
50.1K
Predicting Molecular Geometry02:27

Predicting Molecular Geometry

45.7K
VSEPR Theory for Determination of Electron Pair Geometries
45.7K

You might also read

Related Articles

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

Sort by
Same author

ALG14 Variants Contribute to a Congenital Disorder of Glycosylation Characterized by Congenital Myasthenia and Epilepsy.

HGG advances·2026
Same author

Accuracy of Distal Internal Carotid Artery Contrast Ratio to Infer Proximal Carotid Disease in the Mobile Stroke Unit.

Stroke (Hoboken, N.J.)·2026
Same author

FXN protomutations are the source of pathogenic expanded GAA alleles in Friedreich ataxia and explain its unequal population distribution.

Human molecular genetics·2026
Same author

Re: Stroke Action Plan for Europe 2018-2030 (SAP-E): mid-term review and update.

European stroke journal·2026
Same author

Clinical characteristics and outcomes of tandem lesions involving internal carotid artery occlusion and distal middle cerebral artery occlusion.

Clinical neurology and neurosurgery·2026
Same author

Compound Heterozygote Friedreich Ataxia Patients With Covert Proximal FXN Gene Deletions.

Annals of clinical and translational neurology·2026

Related Experiment Video

Updated: Jan 28, 2026

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping
10:25

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping

Published on: September 25, 2019

49.3K

Deep Learning-Based Prediction of Final Infarct Core from CT Perfusion Data: A Comparison to the Clinical Standard.

Freda Werdiger1,2, Milanka Visser1,2, Chushuang Chen2

  • 1Department of Medicine Dentistry and Health Sciences The University of Melbourne Melbourne Australia.

Stroke (Hoboken, N.J.)
|January 26, 2026
PubMed
Summary
This summary is machine-generated.

A new deep learning model for computed tomography perfusion (CTP) provides a more accurate estimation of the ischemic core in stroke patients. This probabilistic CTP model surpasses traditional single-threshold methods for predicting tissue fate after reperfusion therapy.

Keywords:
acute ischemic strokeartificial intelligencecomputed tomography perfusion imagingdeep learning prediction

More Related Videos

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.8K
Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
07:13

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

Published on: April 18, 2025

504

Related Experiment Videos

Last Updated: Jan 28, 2026

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping
10:25

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping

Published on: September 25, 2019

49.3K
Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.8K
Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
07:13

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

Published on: April 18, 2025

504

Area of Science:

  • Neuroimaging
  • Artificial Intelligence in Medicine
  • Stroke Imaging Analysis

Background:

  • Computed tomography perfusion (CTP) is crucial for assessing ischemic stroke, defining the core and penumbra to guide reperfusion therapy.
  • Current CTP methods rely on single-value thresholds, which may oversimplify complex pathophysiology and discard valuable data.
  • Advancing CTP analysis to a probabilistic model offers enhanced pathophysiological modeling and improved data utilization for estimating tissue fate.

Purpose of the Study:

  • To develop and evaluate a deep learning-based probabilistic CTP model for more accurate estimation of infarct core in acute ischemic stroke.
  • To move beyond the limitations of single-value perfusion thresholds in clinical practice.
  • To improve the prediction of tissue fate after reperfusion therapy in stroke patients.

Main Methods:

  • A retrospective study utilizing the International Stroke Perfusion Imaging Registry database.
  • Development of a deep learning model (Attention U-Net) using the MONAI framework on CTP data from patients with large vessel occlusion, successful thrombectomy, and follow-up imaging.
  • Model training, validation, and testing using distinct data cohorts (n=243 total patients).

Main Results:

  • The Attention U-Net deep learning model demonstrated superior performance in predicting the follow-up infarct core compared to single-value thresholding.
  • The probabilistic CTP model achieved a higher diverse counterfactual explanations score (0.430±0.213) and area under the curve (0.765±0.095) on the test set.
  • These results were statistically significant (P<0.0001) compared to the single-threshold approach (DCE score: 0.247±0.167, AUC: 0.604±0.074).

Conclusions:

  • The developed deep learning probabilistic CTP model significantly outperforms current clinical standards for core estimation in acute ischemic stroke.
  • This probabilistic approach offers a more accurate and sophisticated method for assessing tissue fate compared to traditional single-threshold CTP analysis.
  • The findings support the clinical utility of advanced AI models for improving stroke management and treatment decisions.