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Related Experiment Video

Updated: Jun 8, 2026

3D Modeling of the Lateral Ventricles and Histological Characterization of Periventricular Tissue in Humans and Mouse

3D Modeling of the Lateral Ventricles and Histological Characterization of Periventricular Tissue in Humans and Mouse

Published on: May 19, 2015

Automatic cardiac ventricle segmentation in MR images: a validation study.

Damien Grosgeorge¹, Caroline Petitjean, Jérôme Caudron

¹Université de Rouen, LITIS EA 4108, BP 12, 76801 Saint-Etienne-du-Rouvray, France.

International Journal of Computer Assisted Radiology and Surgery

|September 18, 2010

Summary

This summary is machine-generated.

This study validates an automatic method for segmenting cardiac ventricles in magnetic resonance (MR) images. The region-driven active contours method shows satisfactory performance for cardiac function assessment.

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Area of Science:

Medical Imaging
Cardiovascular Imaging
Image Analysis

Background:

Cardiac ventricle segmentation is crucial for assessing heart function using magnetic resonance (MR) imaging.
Manual delineation for validating segmentation methods is time-consuming, requiring hundreds of images.
Automated methods require rigorous quantitative validation before clinical application.

Purpose of the Study:

To quantitatively validate a well-established automatic segmentation method for cardiac ventricles in MR images.
To assess the performance of region-driven active contours for left and right ventricle segmentation.
To analyze segmentation errors and identify areas for algorithmic improvement.

Main Methods:

An automatic method utilizing active contours without edges was employed for ventricle segmentation.
A database of 1,920 MR images from 59 patients was analyzed.
Two standard metrics were used for quantitative error measurement.

Main Results:

Segmentation results demonstrated comparability to existing literature values.
Performance was superior at end diastole compared to end systole.
Mid-ventricular slices yielded better results than apical slices, with spatial error distribution analyzed.

Conclusions:

Region-driven active contours offer a satisfactory approach for ventricular segmentation in MRI without prior knowledge.
Analysis of error distribution provides insights for enhancing algorithm performance.
The validated method supports accurate cardiac function assessment through MR image analysis.