title: Recent Development of Dual-Dictionary Learning Approach in Medical Image Analysis and Reconstruction.
abstract: As an implementation of compressive sensing (CS), dual-dictionary learning (DDL) method provides an ideal access to restore signals of two related dictionaries and sparse representation. It has been proven that this method performs well in medical image reconstruction with highly undersampled data, especially for multimodality imaging like CT-MRI hybrid reconstruction. Because of its outstanding strength, short signal acquisition time, and low radiation dose, DDL has allured a broad interest in both academic and industrial fields. Here in this review article, we summarize DDL's development history, conclude the latest advance, and also discuss its role in the future directions and potential applications in medical imaging. Meanwhile, this paper points out that DDL is still in the initial stage, and it is necessary to make further studies to improve this method, especially in dictionary training.
authors.affiliation: Department of Engineering Physics, Tsinghua University, Beijing 100084, China ; Key Laboratory of Particle & Radiation Imaging (Tsinghua University), Ministry of Education, Beijing 100084, China.
authors.forename: Bigong
authors.initials: B
authors.lastname: Wang
authors.affiliation: Department of Engineering Physics, Tsinghua University, Beijing 100084, China ; Key Laboratory of Particle & Radiation Imaging (Tsinghua University), Ministry of Education, Beijing 100084, China.
authors.forename: Liang
authors.initials: L
authors.lastname: Li
mesh_terms: D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology / Q000000981:diagnostic imaging; D019295:Computational Biology; D044962:Data Compression / Q000379:methods; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods; D000069550:Machine Learning; D008279:Magnetic Resonance Imaging / Q000706:statistics & numerical data; D025341:Principal Component Analysis; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods; D014057:Tomography, X-Ray Computed / Q000706:statistics & numerical data