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Interactive Image Segmentation Framework Based On Control Theory.

Liangjia Zhu¹, Ivan Kolesov¹, Peter Karasev²

¹Stony Brook University, Stony Brook, New York, USA.

Proceedings of Spie--The International Society for Optical Engineering

|February 23, 2016

Summary

This summary is machine-generated.

This study introduces a control theory approach for interactive medical image segmentation. It uses Lyapunov stability analysis to create a robust and effective system for segmenting anatomical structures.

Keywords:

Active Contours Control Theory Interactive Image Segmentation Lyapunov Stability

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Area of Science:

Medical Imaging
Control Theory
Computer-Aided Diagnosis

Background:

Accurate segmentation of anatomical structures is crucial for clinical applications.
Developing automated methods for diverse imaging modalities and structures remains challenging.

Purpose of the Study:

To present a general design principle for integrating user interactions into medical image segmentation.
To apply control theory, specifically Lyapunov stability analysis, to interactive segmentation systems.

Main Methods:

Formulating interactive segmentation as a control system.
Employing Lyapunov stability analysis for system design and evaluation.
Demonstrating the effectiveness and robustness of the proposed interactive approach.

Main Results:

The proposed control theory framework enables effective user interaction in segmentation.
Lyapunov stability analysis ensures the robustness of the interactive segmentation system.
The method is shown to be effective across various anatomical structures and imaging modalities.

Conclusions:

A novel control theory-based design principle for interactive medical image segmentation is presented.
The integration of user interaction through control theory offers a robust and effective solution.
This approach advances the development of generic segmentation tools for clinical use.