Now showing items 1-5 of 5

    • Compressed Multi-Contrast Magnetic Resonance Image Reconstruction Using Augmented Lagrangian Method 

      Gungor, A.; Kopanoglu, E.; Cukur, T.; Guven, H. E. (Institute of Electrical and Electronics Engineers Inc., 2016)
      In this paper, a Multi-Channel/Multi-Contrast image reconstruction algorithm is proposed. The method, which is based on the Augmented Lagrangian Method uses joint convex objective functions to utilize the mutual information ...
    • Relevance feedback and sparsity handling methods for temporal data 

      Eravcı, Bahaeddin (Bilkent University, 2018-08)
      Data with temporal ordering arises in many natural and digital processes with an increasing importance and immense number of applications. This study provides solutions to data mining problems in analyzing time series ...
    • Sparsity and convex programming in time-frequency processing 

      Deprem, Zeynel (Bilkent University, 2014-12)
      In this thesis sparsity and convex programming-based methods for timefrequency (TF) processing are developed. The proposed methods aim to obtain high resolution and cross-term free TF representations using sparsity and ...
    • Sparsity Based Image Retrieval using relevance feedback 

      Günay O.; Çetin, A.E. (2012)
      In this paper, a Content Based Image Retrieval (CBIR) algorithm employing relevance feedback is developed. After each round of user feedback Biased Discriminant Analysis (BDA) is utilized to find a transformation that best ...
    • Targeted vessel reconstruction in non-contrast-enhanced steady-state free precession angiography 

      Ilicak, E.; Cetin S.; Bulut E.; Oguz, K. K.; Saritas, E. U.; Unal, G.; Çukur, T. (John Wiley and Sons Ltd, 2016)
      Image quality in non-contrast-enhanced (NCE) angiograms is often limited by scan time constraints. An effective solution is to undersample angiographic acquisitions and to recover vessel images with penalized reconstructions. ...