Special Issue "Machine Learning and Compressed Sensing in Image Reconstruction"
Deadline for manuscript submissions: 15 June 2019
The development of fast and accurate reconstruction algorithms plays a central role in modern imaging systems. Examples include x-ray tomography, ultrasound imaging, photoacoustic imaging, super-resolution imaging, and magnetic resonance imaging. Compressed sensing and machine learning are successful tools for various imaging applications. Compressed sensing techniques allow to significantly reduce the amount of data to be acquired and thereby accelerates data acquisition, reduces motion artefacts, and lowers radiation exposure. In compressed sensing, iterative algorithms based on prior information have been applied for image reconstruction. Such algorithms can be time-consuming as the forward and adjoint problems have to be computed repeatedly. Recently, a new class of algorithms based on machine learning, especially deep learning, for compressed sensing and other image reconstruction tasks appeared. With deep learning, image reconstruction can be performed efficiently using artificial neural networks, whose weights are based on training data. While still in their infancy, these techniques already show astonishing performance. This Special Issue focuses on the latest research and development of compressed sensing and machine learning for image reconstruction. Papers on the design of new reconstruction algorithms and new compressed sensing and machine learning applications are welcome. In addition, contributions on the theoretical analysis and understanding of compressed sensing and machine learning in image reconstruction are welcome.
Prof. Dr. Markus Haltmeier
Prof. Dr. Linh. V. Nguyen
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- computed tomography
- compressed sensing
- sampling theory
- iterative algorithms
- photoacoustic tomography
- magnetic resonance imaging
- parameter identification
- regularization methods
- sparse recovery
- neural networks
- deep learning image reconstruction
- data consistency