An automated intelligent diagnostic system for the interpretation of umbilical artery Doppler velocimetry
Abstract
The objective is to develop an automated intelligent diagnostic system for the interpretation of umbilical artery velocity waveforms. An ultrasound instrument with pulsed-wave Doppler is connected to a microcomputer by means of a frame grabber. After data acquisition, umbilical Doppler velocimetry is handled as a pattern recognition (feature extraction and classification) and decision-making problem. Automated image processing (enhancement, smoothing/ thresholding and edge detection) and analysis are used for feature extraction. Six waveform indices obtained by feature extraction are used as input layer to vector quantization which classifies waveforms into six groups. A clinical decision is assigned to each group by the medical expert. Our system is trained by 278 and 380 waveform images of 94 normal and 157 high risk pregnancies, respectively. The system was tested with 193 and 61 images of normal and risky pregnancies; it was demonstrated that sensitivity and specificity of the system are 54.1% and 80.3%, respectively.
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Beksaç et al. and Baykal et al. presented an automated diagnostic, interpretation, and classification method to analyze umbilical artery blood flow Doppler US images.
“In the earliest studies included in this review, Beksaç et al. and Baykal et al. presented an automated diagnostic, interpretation, and classification method to analyze umbilical artery blood flow Doppler US images [124,125,126].”
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- Authors
- Beksaç, M. S., Egemen, A., izzetoǵlu, K., Ergün, G., & Erkmen, A. M.
- Affiliations
- Hacettepe University (TR)
- Middle East Technical University (TR)
- Corresponding author
- Beksaç, M.Sinan
- Venue
- European Journal of Radiology
- Publisher
- Elsevier BV
- Published
- 1996-09
- Volume
- 23
- Issue
- 2
- Pages
- 162-167
- ISSN
- 0720-048X (ISSN-L)
- OpenAlex
- W2018090249
- Cited by
- 8
- References
- 27
- Citations by year
- 2023: 2 · 2020: 1
- FWCI
- 0.00
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- European Journal of Radiology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
- Health Sciences › Medicine › Obstetrics and Gynecology › Pregnancy and preeclampsia studies
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Keywords
- umbilical artery Doppler, pattern recognition, feature extraction, vector quantization, high-risk pregnancy, fetal growth restriction, clinical decision support, image processing, edge detection, thresholding
- MeSH terms
- Artificial Intelligence, Blood Flow Velocity, Decision Making, Diagnosis, Computer-Assisted, Expert Systems, Female, Gestational Age, Humans, Image Enhancement, Image Processing, Computer-Assisted, Microcomputers, Pattern Recognition, Automated, Pregnancy, Pregnancy Complications, Software, Umbilical Arteries, Pregnancy, High-Risk, Ultrasonography, Doppler, Pulsed
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