Güngör, A.Kopanoğlu, E.Çukur, TolgaGüven, E.Yarman-Vural, F. T.2019-02-212019-02-2120189781538653401http://hdl.handle.net/11693/50164Date of Conference: 24 Nov.-26 Dec. 2017This study deals with reconstruction of compressed multicontrast magnetic resonance image (MRI) reconstruction using joint dictionary learning. Usually pre-determined dictionaries are used for compressed sensing reconstructions. Here, we propose an alternating-minimization based algorithm for recovering image and sparsifying transformation from only data itself. The proposed method can also be viewed as a joint multicontrast reconstruction extension of a previous blind compressive sensing algorithm [1]. For evaluation, the algorithm is compared in terms of convergence speed and image quality to both individual dictionary learning based method [1], and a joint reconstruction algorithm using pre-determined dictionaries for MRI [2].TurkishConference Paper10.1109/BIYOMUT.2017.8478900