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Adaptive blood pool segmentation in three-dimensions: application to MR cardiac evaluation
S V Kaushikkar1, D Li, E M Haacke
1Mallinckrodt Institute of Radiology, Washington University, St. Louis, Missouri 63110, USA.
Journal of Magnetic Resonance Imaging : JMRI
|July 1, 1996
Summary
This study introduces an automated method for segmenting cardiac blood pools in MRI scans. The new technique improves accuracy and efficiency in calculating left ventricular blood volumes, aiding cardiac function assessment.
Area of Science:
- Cardiovascular Imaging
- Medical Image Analysis
- Computational Anatomy
Background:
- Cardiac Magnetic Resonance Imaging (MRI) is crucial for assessing global cardiac function.
- Manual segmentation of the cardiac blood pool is time-consuming and operator-dependent, limiting widespread clinical use.
- Accurate segmentation is essential for reliable left ventricular blood volume computation.
Purpose of the Study:
- To develop and evaluate an automated, adaptive threshold-based, 3D region-growing technique for cardiac blood pool segmentation.
- To improve the efficiency and accuracy of left ventricular blood volume calculation from cardiac MRI.
- To reduce operator dependency in cardiac MRI analysis.
Main Methods:
- A novel double segmentation approach incorporating myocardial information was employed.
- Adaptive thresholding and 3D region-growing algorithms were utilized for segmentation.
- The technique was validated against manual segmentation in four human subjects.
Main Results:
- The proposed method demonstrated effective segmentation of the cardiac blood pool from the myocardium.
- The technique requires minimal operator input, showing robustness and user-friendliness.
- Quantitative comparison with manual segmentation confirmed the method's accuracy.
Conclusions:
- Adaptive thresholding combined with multidimensional region-growing is a suitable method for left ventricular blood pool segmentation.
- This automated approach enhances the efficiency and reliability of cardiac MRI for global cardiac function evaluation.
- The technique has the potential to facilitate broader adoption of cardiac MRI in clinical practice.