Browsing by Author "Selver, M.A."

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Evaluation of Waveform Structure Features on Time Domain Target Recognition under Cross Polarization
(IOP PUBLISHING LTD, 2016) M. A. Selver; M. Secmen; E. Y. Zoral; Selver, M.A.; Zoral, E.Y.; Seçmen, M.; EC Vagenas; DS Vlachos
Classification of aircraft targets from scattered electromagnetic waves is a challenging application which suffers from aspect angle dependency. In order to eliminate the adverse effects of aspect angle various strategies were developed including the techniques that rely on extraction of several features and design of suitable classification systems to process them. Recently a hierarchical method which uses features that take advantage of waveform structure of the scattered signals is introduced and shown to have effective results. However this approach has been applied to the special cases that consider only a single planar component of electric field that cause no-cross polarization at the observation point. In this study two small scale aircraft models Boeing-747 and DC-10 are selected as the targets and various polarizations are used to analyse the cross-polarization effects on system performance of the aforementioned method. The results reveal the advantages and the shortcomings of using waveform structures in time-domain target identification.
User aligned histogram stacks for visualization of abdominal organs via MRI
(Institute of Physics Publishing helen.craven@iop.org, 2016) Merve Özdemir; Olcay Akay; Cüneyt Güzeliş; Oĝuz Dicle; Alper Mustafa Selver; Dicle, O.; Özdemir, M.; Güzeliş, C.; Selver, M.A.; Akay, O.; E.C. Vagenas , D.S. Vlachos
Multi-dimensional transfer functions (MDTF) are occasionally designed as two-step approaches. At the first step the constructed domain is modelled coarsely using global volume statistics and an initial transfer function (TF) is designed. Then a finer classification is performed using local information to refine the TF design. In this study both a new TF domain and a novel two-step MDTF strategy are proposed for visualization of abdominal organs. The proposed domain is generated by aligning the histograms of the slices which are reconstructed based on user aligned majority axis/regions through an interactive Multi-Planar Reconstruction graphical user interface. It is shown that these user aligned histogram stacks (UAHS) exploit more a priori information by providing tissue specific inter-slice spatial domain knowledge. For initial TF design UAHS are approximated using a multi-scale hierarchical Gaussian mixture model which is designed to work in quasi real time. Then a finer classification step is carried out for refinement of the initial result. Applications to several MRI data sets acquired with various sequences demonstrate improved visualization of abdomen. © 2018 Elsevier B.V. All rights reserved.