04115nam a22006135i 4500 978-981-4021-96-8 DE-He213 20210622183143.0 cr nn 008mamaa 121029s2013 si | s |||| 0|eng d 9789814021968 978-981-4021-96-8 10.1007/978-981-4021-96-8 doi TK5102.9 TA1637-1638 TTBM bicssc TEC008000 bisacsh TTBM thema UYS thema 621.382 23 Lai, Khin Wee. author. aut http://id.loc.gov/vocabulary/relators/aut Detection of Fetal Abnormalities Based on Three Dimensional Nuchal Translucency [electronic resource] / by Khin Wee Lai, Eko Supriyanto. 1st ed. 2013. Singapore : Springer Singapore : Imprint: Springer, 2013. VIII, 113 p. 93 illus., 64 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda SpringerBriefs in Applied Sciences and Technology, 2191-530X Medicine and Engineering related researches on the utility of two dimensional Nuchal Translucency -- Designs and implementation of three dimensional Nuchal Translucency -- Clinical Tests and measurements -- Future Improvements. Ultrasound (US) prenatal screening has been proposed as the most effective technique for Trisomy 21 early assessment. Assessment of Nuchal Translucency (NT) offers promising non-invasive method for fetal abnormalities detection up to 75%. Nevertheless, current clinician practice of NT examination by locating the sonogram calipers on 2D US image requires highly trained and competent operators by adhering to a standard tedious protocol; therefore it is prone to errors and hence it decreases the reliability in intra- and inter-observer repeatability. This Brief provides the basic knowledge regarding Trisomy 21 diseases and its existing detection methods. The restrictions and disadvantages of each method are discussed accordingly. Therefore, a non-invasive early detection method using 3D ultrasound reconstruction of Nuchal Translucency is introduced. This new method for 3D NT assessments has an edge over the previous 2D methods, and entails the composite function in visualizing the explicit internal marker structure. Further, image processing techniques covered from data acquisition, pre-processing, speckle noise reduction and 3D segmentation are also discussed. This should be especially useful for students and professional researchers in the Biomedical and image processing fields. Signal processing. Image processing. Speech processing systems. Biomedical engineering. Radiology. Medical physics. Radiation. Signal, Image and Speech Processing. https://scigraph.springernature.com/ontologies/product-market-codes/T24051 Biomedical Engineering and Bioengineering. https://scigraph.springernature.com/ontologies/product-market-codes/T2700X Ultrasound. https://scigraph.springernature.com/ontologies/product-market-codes/H29064 Medical and Radiation Physics. https://scigraph.springernature.com/ontologies/product-market-codes/P27060 Imaging / Radiology. https://scigraph.springernature.com/ontologies/product-market-codes/H29005 Supriyanto, Eko. author. aut http://id.loc.gov/vocabulary/relators/aut SpringerLink (Online service) Springer Nature eBook Printed edition: 9789814021975 Printed edition: 9789814021951 SpringerBriefs in Applied Sciences and Technology, 2191-530X https://doi.org/10.1007/978-981-4021-96-8 ZDB-2-ENG ZDB-2-SXE Engineering (SpringerNature-11647) Engineering (R0) (SpringerNature-43712)