UCT Projection Data Estimation

A 2D Compact ultrasound computerized tomography (UCT) system is developed. Fully automatic post-processing tools involving signal and image processing are developed as well. Square of the amplitude values are used in transmission mode with natural 1.5 MHz frequency and rise time 10.4 ns and fall time 8.4 ns and duty cycle of 4.32%. The highest peak to corresponding trough values are considered as transmitting wave between transducers in direct line talk. Sensitivity analysis of methods to extract peak to the corresponding trough per transducer are discussed in this paper. Total fve methods are tested. These methods are taken from broad categories: (a) Conventional and (b) Artifcial Intelligence (AI) based methods. Conventional methods, namely: (a) simple gradient based peak detection, (b) Fourier based, (c) wavelet transform, are compared with AI based methods: (a) support vector machine (SVM), (b) artifcial neural network (ANN). The classifcation step is performed as well to discard the signal which does not has a contribution to the transmission wave. It is found that AI methods have equally good as compared to conventional methods. Reconstruction error, KT 1error estimates, accuracy, F-Score, recall, precision, specifcity and MCC are used. ANN and FFT methods are processing the UCT signal with the best recovery.