A Fuzzy Decision System for Ultrasonic Prenatal Examination Enhancement
نویسندگان
چکیده
We report here on the development of a fuzzy decision system to semi-automate ultrasonic prenatal examinations in order to reduce their cost, minimize exposure time of the fetus to ultrasonic radiation, and to provide a uniform examination for all patients. To our knowledge, this is the first successful application of its kind, and paves the way towards development of a computationally intelligent system for prenatal examination. Obstetric scanning is an established technique for noninvasive examination of the fetus. However, arguments can be made against its routine use. These include the operation’s financial cost, concerns for safety of the developing fetus, and the potential to adversely affect the management of the pregnancy due to misuse or misinterpretation of sonographic findings. Of these, financial cost is probably the most important obstacle to routine scanning. In the United States alone, the cost for one ultrasound examination for each of the 3 million babies born each year would total around $450 million. The potential cost of scanning each pregnancy twice approaches $1 billion per year [1]. The vast majority of “low-risk” obstetric sonograms are performed or supervised by physicians who actually devote a minority of their time to ultrasound and who have relatively little experience in the prenatal diagnosis of congenital malformations. When such examinations are also limited to one or more biometric measurements without a survey of fetal anatomy, many malformations will be missed. Most important in regard to detection of fetal anomalies are standard ultrasound planes and anatomic landmarks that are recommended during the second and third trimesters. Incorporation of these standard views into routine obstetric scanning has the potential to detect or exclude the vast majority of major anomalies [2].
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