Literature DB >> 17946463

Rapid multi-modality preregistration based on SIFT descriptor.

Jian Chen1, Jie Tian.   

Abstract

This paper describes the scale invariant feature transform (SIFT) method for rapid preregistration of medical image. This technique originates from Lowe's method wherein preregistration is achieved by matching the corresponding keypoints between two images. The computational complexity has been reduced when we applied SIFT preregistration method before refined registration due to its O(n) exponential calculations. The features of SIFT are highly distinctive and invariant to image scaling and rotation, and partially invariant to change in illumination and contrast, it is robust and repeatable for cursorily matching two images. We also altered the descriptor so our method can deal with multimodality preregistration.

Mesh:

Year:  2006        PMID: 17946463     DOI: 10.1109/IEMBS.2006.260599

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  4 in total

1.  Intra-operative adjustment of standard planes in C-arm CT image data.

Authors:  Michael Brehler; Joseph Görres; Jochen Franke; Karl Barth; Sven Y Vetter; Paul A Grützner; Hans-Peter Meinzer; Ivo Wolf; Diana Nabers
Journal:  Int J Comput Assist Radiol Surg       Date:  2015-08-28       Impact factor: 2.924

2.  Automatic registration of multi-modal microscopy images for integrative analysis of prostate tissue sections.

Authors:  Giuseppe Lippolis; Anders Edsjö; Leszek Helczynski; Anders Bjartell; Niels Chr Overgaard
Journal:  BMC Cancer       Date:  2013-09-05       Impact factor: 4.430

3.  Possibility Study of Scale Invariant Feature Transform (SIFT) Algorithm Application to Spine Magnetic Resonance Imaging.

Authors:  Dong-Hoon Lee; Do-Wan Lee; Bong-Soo Han
Journal:  PLoS One       Date:  2016-04-11       Impact factor: 3.240

4.  Granular computing in mosaicing of images from capsule endoscopy.

Authors:  Lukasz Maciura; Jan G Bazan
Journal:  Nat Comput       Date:  2015-01-06       Impact factor: 1.690

  4 in total

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