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Brain Imaging

Brain Imaging

Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans), magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...

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Related Experiment Video

Updated: Dec 24, 2025

Author Spotlight: Integrated Photoacoustic, Ultrasound, and Angiographic Tomography (PAUSAT) for NonInvasive Whole-Brain Imaging of Ischemic Stroke

Author Spotlight: Integrated Photoacoustic, Ultrasound, and Angiographic Tomography (PAUSAT) for NonInvasive Whole-Brain Imaging of Ischemic Stroke

Published on: June 2, 2023

Human Brain Atlases in Stroke Management.

Wieslaw L Nowinski¹

¹John Paul II Center for Virtual Anatomy and Surgical Simulation, University of Cardinal Stefan Wyszynski, Woycickiego 1/3, Block 12, room 1220, 01-938, Warsaw, Poland. w.nowinski@uksw.edu.pl.

Neuroinformatics

|April 16, 2020

Summary

Novel brain atlases aid stroke management by improving diagnosis, treatment, and prediction. This patented approach uses multiple atlases for rapid, quantitative assessment, enhancing patient outcomes in stroke care.

Keywords:

CT Diagnosis Human brain atlas MR Neuroimage processing Neuroimaging Prediction Prototype Stroke Treatment Validation

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Last Updated: Dec 24, 2025

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Published on: May 31, 2024

Area of Science:

Neurology
Medical Imaging
Artificial Intelligence

Background:

Stroke is a leading cause of death and disability, with complex management challenges.
Current stroke management involves diverse protocols, imaging, and strict time constraints.
There is a need for efficient and accurate tools to aid in stroke diagnosis and treatment.

Purpose of the Study:

To introduce novel, patented solutions for stroke management using multiple brain atlases.
To demonstrate the application of brain atlases in diagnosis, treatment, and prediction of stroke.
To showcase the potential advantages of atlas-assisted processing in stroke care.

Main Methods:

Utilized diverse CT and MRI scans from various cohorts and patient groups.
Employed brain atlases including anatomy, blood supply territories, and probabilistic stroke atlas.
Developed atlas-to-scan mapping for application-dependent processing of regions of interest (ROIs).

Main Results:

Illustrated the potential of brain atlases in four key applications: stroke prediction, emergency diagnosis, thrombolysis decision support, and outcome prediction.
Demonstrated rapid processing and automated handling of brain scans.
Showcased quantitative assessment capabilities for stroke management.

Conclusions:

Brain atlases offer significant advantages for stroke management, including speed, automation, and quantitative assessment.
The developed atlas-assisted methods show promise for improving stroke diagnosis, treatment, and prediction.
Further clinical validation and development are needed for integration into clinical practice.