English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Retrospective Motion Correction of Magnitude-Input MR Images

Loktyushin, A., Schuler, C., Scheffler, K., & Schölkopf, B. (2016). Retrospective Motion Correction of Magnitude-Input MR Images. In K. Bhatia (Ed.), Machine Learning Meets Medical Imaging (pp. 3-12). Piscataway, NJ, USA: IEEE.

Item is

Basic

show hide
Item Permalink: http://hdl.handle.net/21.11116/0000-0000-7AB4-C Version Permalink: http://hdl.handle.net/21.11116/0000-0000-FA7C-C
Genre: Conference Paper

Files

show Files

Locators

show
hide
Locator:
Link (Any fulltext)
Description:
-

Creators

show
hide
 Creators:
Loktyushin, A1, 2, Author              
Schuler, C1, Author              
Scheffler, K2, 3, Author              
Schölkopf, B1, Author              
Affiliations:
1Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_1497647              
2Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497796              
3Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

Content

show
hide
Free keywords: -
 Abstract: There has been a considerable progress recently in understanding and developing solutions to the problem of image quality deterioration due to patients’ motion in MR scanners. Retrospective methods can be applied to previously acquired motion corrupted data, however, such methods require complex-valued raw volumes as input. It is common practice, though, to preserve only spatial magnitudes of the medical scans, which makes the existing post-processing-based approaches inapplicable. In this work, we make first humble steps towards solving the problem of motion-related artifacts in magnitude-only scans. We propose a learning-based approach, which involves using large-scale convolutional neural networks to learn the transformation from motion-corrupted magnitude observations to the sharp images.

Details

show
hide
Language(s):
 Dates: 2016
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: DOI: 10.1007/978-3-319-27929-9_1
BibTex Citekey: LoktyushinSSS2016
 Degree: -

Event

show
hide
Title: First International Workshop on Machine Learning Meets Medical Imaging (MLMMI 2015), held in conjunction with ICML 2015
Place of Event: Lille, France
Start-/End Date: -

Legal Case

show

Project information

show

Source 1

show
hide
Title: Machine Learning Meets Medical Imaging
Source Genre: Proceedings
 Creator(s):
Bhatia , K.K., Editor
Lombaert, H., Author
Affiliations:
-
Publ. Info: Piscataway, NJ, USA : IEEE
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 3 - 12 Identifier: ISBN: 978-3-319-27928-2

Source 2

show
hide
Title: Lecture Notes in Computer Science ; 9487
Source Genre: Series
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: - Identifier: -