Comparing Different Compressed Sensing Reconstruction Techniques for the System Matrix in Single-Sided MPI

Patrick Weissert; Anselm von Gladiß; Thorsten M. Buzug

Comparing Different Compressed Sensing Reconstruction Techniques for the System Matrix in Single-Sided MPI

Patrick Weissert
, Anselm von Gladiß
, Thorsten M. Buzug

Institute of Medical Engineering

Original language	English
Title of host publication	Student Conference Proceedings 2016
Editors	Thorsten Buzug, Heinz Handels
Number of pages	4
Publisher	Infinite Science Publishing
Publication date	09.03.2016
Pages	225-228
ISBN (Print)	978-3-945954-18-8
Publication status	Published - 09.03.2016
Event	Student Conference 2016, Medical Engineering Science and Medical Informatics - Lübeck, Germany Duration: 09.03.2016 → 11.03.2016

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being
SDG 9 Industry, Innovation, and Infrastructure

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https://books.infinite-science.de/tagungsbaende/222/student-conference-proceedings-2016

Optimized Data Acquisition for Image Reconstruction in Magnetic Particle Imaging (MPI) Based on Compressed Sensing
Buzug, T. (Principal Investigator (PI)) & Mertins, A. (Principal Investigator (PI))
01.01.14 → 31.12.19
Project: DFG Individual Projects

Cite this

Weissert, P., von Gladiß, A., & Buzug, T. M. (2016). Comparing Different Compressed Sensing Reconstruction Techniques for the System Matrix in Single-Sided MPI. In T. Buzug, & H. Handels (Eds.), Student Conference Proceedings 2016 (pp. 225-228). (Student Conference Proceedings). Infinite Science Publishing. https://books.infinite-science.de/tagungsbaende/222/student-conference-proceedings-2016

@inproceedings{c393ecb449f34e5982f71ad18e5f85e2,

title = "Comparing Different Compressed Sensing Reconstruction Techniques for the System Matrix in Single-Sided MPI",

author = "Patrick Weissert and \{von Gladi{\ss}\}, Anselm and Buzug, \{Thorsten M.\}",

year = "2016",

month = mar,

day = "9",

language = "English",

isbn = "978-3-945954-18-8",

series = "Student Conference Proceedings",

publisher = "Infinite Science Publishing",

pages = "225--228",

editor = "Thorsten Buzug and Heinz Handels",

booktitle = "Student Conference Proceedings 2016",

note = "Student Conference 2016, Medical Engineering Science and Medical Informatics<br/> ; Conference date: 09-03-2016 Through 11-03-2016",

}

Weissert, P, von Gladiß, A & Buzug, TM 2016, Comparing Different Compressed Sensing Reconstruction Techniques for the System Matrix in Single-Sided MPI. in T Buzug & H Handels (eds), Student Conference Proceedings 2016. Student Conference Proceedings, Infinite Science Publishing, pp. 225-228, Student Conference 2016, Medical Engineering Science and Medical Informatics
, Lübeck, Germany, 09.03.16. <https://books.infinite-science.de/tagungsbaende/222/student-conference-proceedings-2016>

Comparing Different Compressed Sensing Reconstruction Techniques for the System Matrix in Single-Sided MPI. / Weissert, Patrick; von Gladiß, Anselm; Buzug, Thorsten M.
Student Conference Proceedings 2016. ed. / Thorsten Buzug; Heinz Handels. Infinite Science Publishing, 2016. p. 225-228 (Student Conference Proceedings).

Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

TY - GEN

T1 - Comparing Different Compressed Sensing Reconstruction Techniques for the System Matrix in Single-Sided MPI

AU - Weissert, Patrick

AU - von Gladiß, Anselm

AU - Buzug, Thorsten M.

PY - 2016/3/9

Y1 - 2016/3/9

M3 - Conference contribution

SN - 978-3-945954-18-8

T3 - Student Conference Proceedings

SP - 225

EP - 228

BT - Student Conference Proceedings 2016

A2 - Buzug, Thorsten

A2 - Handels, Heinz

PB - Infinite Science Publishing

T2 - Student Conference 2016, Medical Engineering Science and Medical Informatics<br/>

Y2 - 9 March 2016 through 11 March 2016

ER -

Comparing Different Compressed Sensing Reconstruction Techniques for the System Matrix in Single-Sided MPI

UN SDGs

Access to Document

Projects

Optimized Data Acquisition for Image Reconstruction in Magnetic Particle Imaging (MPI) Based on Compressed Sensing

Cite this