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Mike Fornefett

dblp:36/3041 · DBLP profile ↗
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3ranked-venue papers
2as first author
0since 2021 · last 2003
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 3 · 2 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Image and video processing · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Image and video processing › image registration
elastic matching		 0.011999
Elastic Registration of Medical Images Using Radial Basis Functions with Compact Support · CVPR 1999
Image and video processing › image registration
medical image registration		 0.011999
Elastic Registration of Medical Images Using Radial Basis Functions with Compact Support · CVPR 1999

Methods — techniques the papers use, named apart from their topics

radial basis functions with compact support · 0.0
YearPublicationVenuePosition
2003 Spline-based elastic image registration: integration of landmark errors and orientation attributes
Karl Rohr, Mike Fornefett, H. Siegfried Stiehl
 Comput. Vis. Image Underst.2
2001 Radial basis functions with compact support for elastic registration of medical images
Mike Fornefett, Karl Rohr, H. Siegfried Stiehl
 Image Vis. Comput.1
1999 Elastic Registration of Medical Images Using Radial Basis Functions with Compact Support
abstract
We introduce radial basis functions with compact support for elastic registration of medical images. With these basis functions the influence of a landmark on the registration result is limited to a circle in 2D and, respectively, to a sphere in 3D. Therefore, the registration can be locally constrained which especially allows to deal with rather local changes in medical images due to, e.g., tumor resection. An important property of the used RBFs is that they are positive definite. Thus, the solvability of the resulting system of equations is always guaranteed. We demonstrate our approach for synthetic as well as for 2D and 3D tomographic images.
Mike Fornefett, Karl Rohr, H. Siegfried Stiehl
 CVPR1