Ultrasound Transducer Quality Control and Performance Evaluation Using Image Metrics Amr A. Sharawy 1(&) , Kamel K. Mohammed 2 , Mohamed Aouf 3 , and Mohammed A.-M. Salem 4,5 1 Biomedical Engineering and System Department, Cairo University, Cairo, Egypt amrarsh@gmail.com 2 Center for Virus Research and Studies, Al-Azhar University, Cairo, Egypt k.eel@hotmail.com 3 Biomedical Engineering Department, HTI, Tenth of Ramadan City, Egypt maoufmedical@yahoo.com 4 Faculty of Computer and Information Sciences, Ain Shams University, Cairo, Egypt salem@cis.asu.edu.eg 5 German University in Cairo, Cairo, Egypt mohammed.salem@guc.edu.eg Abstract. This paper aims to two main goals, first goal is to achieve the characterization of quality control of ultrasound scanners based on the potential image metrics. On the other hand, the most effective goal is how to classify ultrasound scanners based on image metrics to evaluate performance of ultra- sound transducer. The authors utilize the metrics to give information about the spatial arrangement of the gray levels in the specific interest region. The exe- cution of ultrasound images metric based on a set of 19 metrics (i.e. contrast, gradient and Laplacian). This set reflects quality control of ultrasound scanners. The wok of this paper based on the best 6 metrics from 19 metrics which extracted from linear discriminative analysis (LDA). The classification methods used for minimum numbers of metrics are fused using support vector machine (SVM) and the highest classification method is back propagation neural network (BPNN) classifiers to get the main target of paper. Finally, the results show that objective performance evaluation of ultrasound transducer accuracy was 100% by using back propagation neural network classifier. Keywords: Focal lesion Á Contrast Á Resolution Á Speckle noise Phantom 1 Introduction Quality control is most invaluable to estimate image quality and machine precision both during the presentation of a modern technology and with regard to performance constancy of over time. Quality control of various ultrasound units is performed on the basis of detection of focal lesions against background tissue because of high spatial resolution and contrast sensitivity requirements [1]. Spatial resolution is defined in © Springer Nature Switzerland AG 2019 A. E. Hassanien et al. (Eds.): AISI 2018, AISC 845, pp. 26–39, 2019. https://doi.org/10.1007/978-3-319-99010-1_3