6533b858fe1ef96bd12b58aa

RESEARCH PRODUCT

A non-supervised approach to locate and to measure the nuchal translucency by means of wavelet analysis and neural networks

Giuseppa SciortinoCesare ValentiDomenico Tegolo

subject

Control and OptimizationArtificial neural networkSettore INF/01 - InformaticaComputer sciencebusiness.industrymid-sagittal sectionneural networksymmetry transformPattern recognitionMeasure (mathematics)Ultrasonic imagingClinical ultrasoundWaveletComputer Networks and CommunicationNuchal translucencyRobustness (computer science)Artificial IntelligenceUltrasound imagingArtificial intelligencewavelet analysibusinessnuchal translucencyInformation Systems

description

Ultrasound imaging is a well known noninvasive way to evaluate various diseases during the prenatal age. In particular, the thickness measure of the nuchal transucency is strictly correlated with pathologies like trisomy 13, 18 and 21. For a correct investigation, the methodology needs mid-sagittal sections and the proposed approach is based on wavelet analysis and neural network classifiers to locate components useful to identify mid-sagittal planes. To evaluate the performance and the robustness of the methodology, real clinical ultrasound images were considered, obtaining an average error of at most 0.3 millimeters in 97.4% of the cases.

10.1109/icat.2017.8171631http://hdl.handle.net/10447/289995