IVCVSep 26, 2019

Segmentation of points of interest during fetal cardiac assesment in the first trimester from color Doppler ultrasound

arXiv:1909.11903v13 citations
Originality Synthesis-oriented
AI Analysis

This is an incremental improvement for obstetricians in fetal cardiac screening.

The study tackled the problem of segmenting points of interest in fetal cardiac assessment from first-trimester color Doppler ultrasound by using Zernike moments for feature extraction and a distance-based approach for classification, resulting in a computational tool that shows promise for rapid recognition of heart views during screening.

The present paper puts forward an incipient study that uses a traditional segmentation method based on Zernike moments for extracting significant features from frames of fetal echocardiograms from first trimester color Doppler examinations. A distance based approach is then used on the obtained indicators to classify frames of three given categories that should be present in a normal heart condition. The computational tool shows promise in supporting the obstetrician in a rapid recognition of heart views during screening.

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