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Related Experiment Video

Updated: Jun 25, 2026

A Volumetric Method for Quantification of Cerebral Vasospasm in a Murine Model of Subarachnoid Hemorrhage

A Volumetric Method for Quantification of Cerebral Vasospasm in a Murine Model of Subarachnoid Hemorrhage

Published on: July 28, 2018

Semi-automated method for brain hematoma and edema quantification using computed tomography.

A Bardera¹, I Boada, M Feixas

¹University of Girona, Girona, Spain. anton.bardera@ima.udg.edu

Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society

|March 10, 2009

Summary

This summary is machine-generated.

This study introduces a semi-automated method for segmenting brain hematoma and edema using computed tomography (CT) scans. The novel approach offers accurate and reproducible results faster than manual segmentation.

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Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

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Area of Science:

Medical Imaging
Neurosurgery
Computational Anatomy

Background:

Brain hematoma and edema segmentation are crucial for diagnosis and treatment planning.
Manual segmentation is time-consuming and prone to inter-observer variability.
Accurate volume measurement aids in assessing disease progression and treatment efficacy.

Purpose of the Study:

To present a semi-automated method for segmenting brain hematoma and edema from computed tomography (CT) images.
To enable accurate and reproducible volume measurement of these brain pathologies.
To reduce the time required for segmentation compared to manual methods.

Main Methods:

A hybrid approach combining region growing for hematoma segmentation and level set segmentation for edema.
Novel strategy for defining the propagation function in the level set method.
Validation on 18 patient CT datasets with varying hematoma and edema characteristics.

Main Results:

The semi-automated method achieved objective and reproducible segmentations.
Segmentation results closely matched those obtained through manual delineation.
Processing time was significantly reduced to approximately 4 minutes from 10 minutes for manual segmentation.

Conclusions:

The proposed semi-automated method provides an efficient and reliable tool for brain hematoma and edema segmentation and volume measurement.
This technique has the potential to improve clinical workflow and patient care in neurocritical settings.
The method's accuracy and speed offer a significant advantage over traditional manual segmentation approaches.