Paper
27 March 2009 Improving an affine and non-linear image registration and/or segmentation task by incorporating characteristics of the displacement field
Konstantin Ens, Stefan Heldmann, Jan Modersitzki, Bernd Fischer
Author Affiliations +
Proceedings Volume 7259, Medical Imaging 2009: Image Processing; 725932 (2009) https://doi.org/10.1117/12.811139
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States
Abstract
Image registration is an important and active area of medical image processing. Given two images, the idea is to compute a reasonable displacement field which deforms one image such that it becomes similar to the other image. The design of an automatic registration scheme is a tricky task and often the computed displacement field has to be discarded, when the outcome is not satisfactory. On the other hand, however, any displacement field does contain useful information on the underlying images. It is the idea of this note, to utilize this information and to benefit from an even unsuccessful attempt for the subsequent treatment of the images. Here, we make use of typical vector analysis operators like the divergence and curl operator to identify meaningful portions of the displacement field to be used in a follow-up run. The idea is illustrated with the help of academic as well as a real life medical example. It is demonstrated on how the novel methodology may be used to substantially improve a registration result and to solve a difficult segmentation problem.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Konstantin Ens, Stefan Heldmann, Jan Modersitzki, and Bernd Fischer "Improving an affine and non-linear image registration and/or segmentation task by incorporating characteristics of the displacement field", Proc. SPIE 7259, Medical Imaging 2009: Image Processing, 725932 (27 March 2009); https://doi.org/10.1117/12.811139
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KEYWORDS
Image registration

Image segmentation

Tumors

Medical imaging

Distance measurement

Image processing

Lung cancer

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