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Computerized automatic nasal bone detection based on ultrasound fetal images using cross correlation techniques

Lai, Khin Wee and Arooj, Adeela and Supriyanto, Eko (2010) Computerized automatic nasal bone detection based on ultrasound fetal images using cross correlation techniques. Wseas Transactions on Information Science and Applications, 7 (8). 1068 - 1077. ISSN 1790-0832

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Abstract

Recent study shows that fetal chromosomal abnormalities can be detected in early ultrasonic prenatal screening by identifying the absence of fetus nasal bone. The drawbacks of current method are operator dependent, observer variability and improper training. In particular, accurate nasal bone detection requires highly trained sonographers, obstetricians and fetal medicine specialists since the ultrasound markers may easily confuse with noise and echogenic line in ultrasound image background. We present a computerized method of detecting the absence of nasal bone by using normalized grayscale cross correlation techniques. Image preprocessing is implemented prior to cross correlation to assess the availability of nasal bone. The resultant threshold, bordering the absence and presence of nasal bone, is set to a value of 0.35. The accuracy of the developed algorithm achieved was, around 96.26 percent which promises an efficient method to recognize nasal bone automatically. The threshold can be further improved if a larger set of nasal bone ultrasound images are applied.

Item Type:Article
Uncontrolled Keywords:matching, nasal bone, trisomy
Subjects:R Medicine > RG Gynecology and obstetrics
Divisions:Science
ID Code:25085
Deposited By: Narimah Nawil
Deposited On:20 Sep 2017 13:08
Last Modified:22 Mar 2018 18:32

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