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Updated: Jun 13, 2026
3D Whole-heart Myocardial Tissue Analysis
Published on: April 12, 2017
3D cardiac segmentation using temporal correlation of radio frequency ultrasound data
Maartje M Nillesen1, Richard G P Lopata, Henkjan J Huisman
1Clinical Physics Laboratory, Department of Pediatrics, Radboud University Nijmegen Medical Centre. m.m.nillesen@cukz.umcn.nl
Insights
This study introduces a new semi-automatic method using radio frequency (rf) ultrasound phase data to segment the heart
Area of Science:
- Medical imaging
- Cardiology
- Ultrasound technology
Background:
- Segmentation of 3D echocardiographic images is crucial for diagnosing heart disease, especially in pediatric congenital cases.
- Challenges include poor echogenicity contrast and speckle noise, limiting accuracy.
- Existing methods struggle when a priori cardiac shape knowledge is unavailable.
Purpose of the Study:
- To develop and evaluate a semi-automatic segmentation method for 3D echocardiographic images.
- To leverage radio frequency (rf) ultrasound phase information for improved segmentation.
- To address segmentation difficulties in pediatric congenital heart disease.
Main Methods:
- A semi-3D technique was employed to calculate local maximum temporal cross-correlation from rf data.
- Maximum cross-correlation values were integrated as an external force into a deformable model.
- The approach was tested against and combined with adaptive filtered, demodulated rf data.
Main Results:
- The novel method demonstrated potential for segmenting the endocardial surface.
- Integration of rf phase information improved segmentation accuracy in challenging regions.
- The technique was validated on full volume images from healthy children.
Conclusions:
- Semi-automatic segmentation using rf ultrasound phase data shows promise for cardiac diagnosis.
- This method offers a valuable tool for pediatric congenital heart disease assessment.
- Further research can refine this technique for broader clinical application.
Abstract:
Semi-automatic segmentation of the myocardium in 3D echographic images may substantially support clinical diagnosis of heart disease. Particularly in children with congenital heart disease, segmentation should be based on the echo features solely since a priori knowledge on the shape of the heart cannot be used. Segmentation of echocardiographic images is challenging because of the poor echogenicity contrast between blood and the myocardium in some regions and the inherent speckle noise from randomly backscattered echoes. Phase information present in the radio frequency (rf) ultrasound data might yield useful, additional features in these regions. A semi-3D technique was used to determine maximum temporal cross-correlation values locally from the rf data. To segment the endocardial surface, maximum cross-correlation values were used as additional external force in a deformable model approach and were tested against and combined with adaptive filtered, demodulated rf data. The method was tested on full volume images (Philips, iE33) of four healthy children and evaluated by comparison with contours obtained from manual segmentation.
