Registration of ultrasonography sequences based on temporal regions

Sebastian Schäfer, Paolo Angelelli, Kim Nylund, Odd Helge Gilja, Klaus Tönnies

INPROCEEDINGS, Proc. Intl. Symp. Image and Signal Processing and Analysis (ISPA), 2011

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Abstract

2D Ultrasonography images with parallel contrast enhanced sequences for analysis constitute a rapid and inexpensive imaging technique with high temporal resolution to assess perfusion of tissue. However, motion from various influences corrupts the inter-pixel correspondences between different time frames and therefore hampers computer-assisted analysis of perfusion parameters. We present a user-supported method applying a temporal similarity matrix to remove frames with uncorrectable out-of-plane motion. For the remaining regions of frames, motion influence can be compensated for by image registration. Subsequently B-Spline based registration is applied using the temporal regions with automatic determination of a suitable reference frame image. Evaluation with ground truth data of six datasets comparing a medical expert frame analysis to the proposed technique yields 85.1% sensitivity and 81.7% specificity in average. On average 6% of the frames have been erroneously included in temporal regions, although they contain out-of-plane motion.

Published

Proc. Intl. Symp. Image and Signal Processing and Analysis (ISPA)

• Pages: 749–754
• Location: Dubrovnik, Croatia
• URL: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6046702

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BibTeX

@inproceedings{schaefer11registration,
 title =  {Registration of ultrasonography sequences based on temporal regions},
 author = {Sebastian Sch{\"a}fer and Paolo Angelelli and Kim Nylund and Odd Helge Gilja and Klaus T{\"o}nnies},
 booktitle = {Proc. Intl. Symp. Image and Signal Processing and Analysis (ISPA)},
 year =  {2011},
 pages =  {749--754},
 abstract = {2D Ultrasonography images with parallel contrast enhanced 
 sequences for analysis constitute a rapid and inexpensive imaging 
 technique with high temporal resolution to assess perfusion of tissue. 
 However, motion from various influences corrupts the inter-pixel 
 correspondences between different time frames and therefore hampers 
 computer-assisted analysis of perfusion parameters. We present a 
 user-supported method applying a temporal similarity matrix to remove 
 frames with uncorrectable out-of-plane motion. For the remaining 
 regions of frames, motion influence can be compensated for by image 
 registration. Subsequently B-Spline based registration is applied 
 using the temporal regions with automatic determination of a suitable 
 reference frame image. Evaluation with ground truth data of six 
 datasets comparing a medical expert frame analysis to the proposed 
 technique yields 85.1% sensitivity and 81.7% specificity in average. 
 On average 6% of the frames have been erroneously included in temporal 
 regions, although they contain out-of-plane motion.},
 location = {Dubrovnik, Croatia},
 url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6046702},


}