title: Medical image registration using sparse coding of image patches.
abstract: Image registration is a basic task in medical image processing applications like group analysis and atlas construction. Similarity measure is a critical ingredient of image registration. Intensity distortion of medical images is not considered in most previous similarity measures. Therefore, in the presence of bias field distortions, they do not generate an acceptable registration. In this paper, we propose a sparse based similarity measure for mono-modal images that considers non-stationary intensity and spatially-varying distortions. The main idea behind this measure is that the aligned image is constructed by an analysis dictionary trained using the image patches. For this purpose, we use "Analysis K-SVD" to train the dictionary and find the sparse coefficients. We utilize image patches to construct the analysis dictionary and then we employ the proposed sparse similarity measure to find a non-rigid transformation using free form deformation (FFD). Experimental results show that the proposed approach is able to robustly register 2D and 3D images in both simulated and real cases. The proposed method outperforms other state-of-the-art similarity measures and decreases the transformation error compared to the previous methods. Even in the presence of bias field distortion, the proposed method aligns images without any preprocessing.
authors.affiliation: Department of Electrical Engineering, Biomedical Signal and Image Processing Laboratory (BiSIPL), Sharif University of Technology, Tehran, Iran. Electronic address: afzali@ee.sharif.edu.
authors.forename: Maryam
authors.initials: M
authors.lastname: Afzali
authors.affiliation: Department of Electrical Engineering, Biomedical Signal and Image Processing Laboratory (BiSIPL), Sharif University of Technology, Tehran, Iran. Electronic address: aboozar412@gmail.com.
authors.forename: Aboozar
authors.initials: A
authors.lastname: Ghaffari
authors.affiliation: Department of Electrical Engineering, Biomedical Signal and Image Processing Laboratory (BiSIPL), Sharif University of Technology, Tehran, Iran. Electronic address: fatemizadeh@sharif.edu.
authors.forename: Emad
authors.initials: E
authors.lastname: Fatemizadeh
authors.affiliation: Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran; School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran; Image Analysis Laboratory, Departments of Radiology and Research Administration, Henry Ford Health System, Detroit, MI, USA. Electronic address: hszadeh@ut.ac.ir.
authors.forename: Hamid
authors.initials: H
authors.lastname: Soltanian-Zadeh
mesh_terms: D003952:Diagnostic Imaging; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008297:Male
keywords: Analysis K-SVD algorithm; Non-rigid image registration; Sparse coding