An automated intelligent diagnostic system for the interpretation of umbilical artery Doppler velocimetry |
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| Institution: | 1. Department of Obstetrics and Gynecology, Kartal Dr. Lutfi Kirdar Education and Research Hospital, Istanbul, Turkey;2. Department of Obstetrics and Gynecology, Zeynep Kamil Education and Research Hospital, Istanbul, Turkey;3. Division of Reproductive Endocrinology and Infertility, Department of Obstetrics, Gynecology and Reproductive Sciences, Yale University School of Medicine, New Haven, CT, USA;4. Department of Obstetrics and Gynecology, Tepecik Education and Research Hospital, Izmir, Turkey;5. Department of Pathology, Zeynep Kamil Education and Research Hospital, Istanbul, Turkey;6. Department of Biochemistry, Cumhuriyet University, Faculty of Pharmacy, Sivas, Turkey;1. The 16th Ward, Department of Ear, Nose and Throat (ENT), Daqing Oilfield General Hospital, Zhongkang Street No. 9, Saertu District, 163000, Daqing City, Heilongjiang Province, China;2. Department of Stomatology, Northeast Petroleum University Affiliated Hospital, Fazhan Road, High Tech District, 163000 Daqing City, Heilongjiang Province, China;3. Department of Stomatology, The Heping Affiliated Hospital of Changzhi Medical College, Changzhi City, Shanxi Province, China;4. Faculty of Dentistry, University of Hong Kong, Hong Kong, China;5. Dr D Y Patil Dental College and Hospital, Dr D Y Patil Vidyapeeth, Pimpri, Pune, India;6. Department of Cariology, Endodontology and Periodontology, University Leipzig, Liebigstr. 12, 04103 Leipzig, Germany;7. Saxon Incubator for Clinical Translation/Translational Centre for Regenerative Medicine, Leipzig University, Phillip-Rosenthal-Str. 55, Leipzig 04103, Germany;8. Genomap Technologies, Kongjiang Road 1500, Yangpu District, Shanghai, China;9. School of Dentistry, University of Michigan, USA;10. Heart Center Leipzig, University of Leipzig, Strümpellstr. 39, 04289 Leipzig, Germany;11. Laboratory of Molecular Cell Biology, Beijing Tibetan Hospital, China Tibetology Research Center, 218 Anwaixiaoguanbeili Street, Chaoyang, Beijing 100029, China;1. Department of Physiology and Pathophysiology, University of Manitoba, Canada;2. Department of Human Nutritional Sciences, University of Manitoba, Canada;3. Canadian Centre for Agri-Food Research in Health and Medicine, St. Boniface Hospital Research Centre, Winnipeg, Canada |
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| 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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