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Updated: Jun 14, 2026

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

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Published on: May 19, 2015

Left Ventricle Segmentation Using Model Fitting and Active Surfaces.

Peter C Tay¹, Bing Li, Chris D Garson

¹Dept. of Electrical and Computer Engineering Technology, Western Carolina University, Cullowhee, NC 28723 USA.

Journal of Signal Processing Systems

|March 20, 2010

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This study presents an improved 4D (3D over time) segmentation method for mouse left ventricles using novel despeckling and locally fitted superellipsoid models. The enhanced technique offers more accurate cardiac segmentation for research applications.

Area of Science:

Biomedical Engineering
Medical Imaging
Cardiovascular Research

Background:

Accurate 4D segmentation of the left ventricle is crucial for understanding cardiac function.
Existing methods often struggle with image noise and initialization challenges.

Purpose of the Study:

To develop an improved 4D segmentation method for the mouse left ventricle.
To enhance segmentation accuracy through novel despeckling and initialization techniques.

Main Methods:

Incorporation of temporal propagation, gradient vector flow active surface, and superquadric models.
Introduction of a novel despeckling method for B-mode cine slices.
Utilizing locally fitted superellipsoid models for improved active surface initialization.

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Reduction in Left Ventricular Wall Stress and Improvement in Function in Failing Hearts using Algisyl-LVR

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Published on: April 8, 2013

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Last Updated: Jun 14, 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

Reduction in Left Ventricular Wall Stress and Improvement in Function in Failing Hearts using Algisyl-LVR

Reduction in Left Ventricular Wall Stress and Improvement in Function in Failing Hearts using Algisyl-LVR

Published on: April 8, 2013

Main Results:

Demonstration of improved surface segmentation accuracy compared to manual segmentation.
Quantitative analysis of average distances throughout the cardiac cycle and cross-sectional contours.
Validation of enhanced initialization for active surface segmentation.

Conclusions:

The proposed 4D segmentation method significantly improves accuracy for mouse left ventricle segmentation.
Novel despeckling and locally fitted superellipsoid models enhance initialization and overall performance.
This method provides a more reliable tool for in vivo cardiovascular research.