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Publication Metadata only Denoising embolic Doppler ultrasound signals using Dual Tree Complex Discrete Wavelet Transform(2010) Serbes, Görkem; Aydın, Nizamettin; Serbes, Görkem, Department of Electrical Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey; Aydın, Nizamettin, Department of Computer Engineering, Yıldız Teknik Üniversitesi, Istanbul, TurkeyEarly and accurate detection of asymptomatic emboli is important for monitoring of preventive therapy in stroke-prone patients. One of the problems in detection of emboli is the identification of an embolic signal caused by very small emboli. The amplitude of the embolic signal may be so small that advanced processing methods are required to distinguish these signals from Doppler signals arising from red blood cells. In this study instead of conventional discrete wavelet transform, the Dual Tree Complex Discrete Wavelet Transform was used for denoising embolic signals. Performances of both approaches were compared. Unlike the conventional discrete wavelet transform discrete complex wavelet transform is a shift invariant transform with limited redundancy. Results demonstrate that the Dual Tree Complex Discrete Wavelet Transform based denoising outperforms conventional discrete wavelet denoising. Approximately 8 dB improvement is obtained by using the Dual Tree Complex Discrete Wavelet Transform compared to the improvement provided by the conventional Discrete Wavelet Transform (less than 5 dB). © 2010 IEEE. © 2011 Elsevier B.V., All rights reserved.Publication Metadata only Directional dual-tree complex wavelet packet transform(2013) Serbes, Görkem; Aydın, Nizamettin; Gülçür, Halil Ö.; Serbes, Görkem, Department of Biomedical Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey, Institute of Biomedical Engineering, Boğaziçi Üniversitesi, Bebek, Turkey; Aydın, Nizamettin, Department of Computer Engineering, Yıldız Teknik Üniversitesi, Istanbul, Turkey; Gülçür, Halil Ö., Institute of Biomedical Engineering, Boğaziçi Üniversitesi, Bebek, TurkeyDoppler ultrasound systems, which are widely used in cardiovascular disorders detection, have quadrature format outputs. Various types of algorithms were described in literature to process quadrature Doppler signals (QDS), such as phasing filter technique (PFT), fast Fourier transform method, frequency domain Hilbert transform method and complex continuous wavelet transform. However for the discrete wavelet transform (DWT) case, which becomes a common method for processing QDSs, there was not a direct method to recover flow direction from quadrature signals. Traditionally, to process QDSs with DWT, firstly directional signals have to be extracted and later two DWTs must be applied. Although there exists a complex DWT algorithm called dual tree complex discrete wavelet transform (DTCWT), it does not provide directional signal decoding during analysis because of the unwanted energy leaks into its negative frequency bands. Modified DTCWT, which is a combination of PFT and DTCWT, has the capability of extracting directional information while decomposing QDSs into different frequency bands, but it uses an additional Hilbert transform filter and it increases the computational complexity of whole transform. Discrete wavelet packet transform (DWPT), which is a generalization of the ordinary DWT allowing subband analysis without the constraint of dyadic decomposition, can perform an adaptive decomposition of the frequency axis. In this study, a novel complex DWPT, which maps directional information while processing QDSs, is proposed. The success of proposed method will be measured by using simulated quadrature signals. © 2013 IEEE. © 2013 Elsevier B.V., All rights reserved.Publication Metadata only Compression of the CT images using classified energy and pattern blocks(2013) Gökbay, İnci Zaim; Gezer, Murat; Güz, Ümit; Gürkan, Hakan; Yarman, Binboǧa Siddik; Gökbay, İnci Zaim, Department of Mechanics, Bahçeşehir Üniversitesi, Istanbul, Turkey; Gezer, Murat, Department of Informatics, Istanbul Üniversitesi, Istanbul, Turkey; Güz, Ümit, Department of Electrical and Electronic Engineering, Işik Üniversitesi, Istanbul, Turkey; Gürkan, Hakan, Department of Electrical and Electronic Engineering, Işik Üniversitesi, Istanbul, Turkey; Yarman, Binboǧa Siddik, Department of Electrical and Electronic Engineering, Işik Üniversitesi, Istanbul, TurkeyIn this work, a new biomedical image compression method is proposed based on the classified energy and pattern blocks (CEPB). CEPB based compression method is specifically applied on the Computed Tomography (CT) images and the evaluation results are presented. Essentially, the CEPB is uniquely designed and structured codebook which is located on the both the transmitter and receiver part of a communication system in order to implement encoding and decoding processes. The encoding parameters are block scaling coefficient (BSC) and the index numbers of energy (IE) and pattern blocks (IP) determined for each block of the input images based on the CEPB. The evaluation results show that the newly proposed method provides considerable image compression ratios and image quality. © 2013 IEEE. © 2013 Elsevier B.V., All rights reserved.Publication Metadata only Directional dual-tree rational-dilation complex wavelet transform(Institute of Electrical and Electronics Engineers Inc., 2014) Serbes, Görkem; Gülçür, Halil Ö.; Aydın, Nizamettin; Serbes, Görkem, Department of Biomedical Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey; Gülçür, Halil Ö., Institute of Biomedical Engineering, Boğaziçi Üniversitesi, Bebek, Turkey; Aydın, Nizamettin, Department of Computer Engineering, Yıldız Teknik Üniversitesi, Istanbul, TurkeyDyadic discrete wavelet transform (DWT) has been used successfully in processing signals having non-oscillatory transient behaviour. However, due to the low Q-factor property of their wavelet atoms, the dyadic DWT is less effective in processing oscillatory signals such as embolic signals (ESs). ESs are extracted from quadrature Doppler signals, which are the output of Doppler ultrasound systems. In order to process ESs, firstly, a pre-processing operation known as phase filtering for obtaining directional signals from quadrature Doppler signals must be employed. Only then, wavelet based methods can be applied to these directional signals for further analysis. In this study, a directional dual-tree rational-dilation complex wavelet transform, which can be applied directly to quadrature signals and has the ability of extracting directional information during analysis, is introduced. © 2021 Elsevier B.V., All rights reserved.