Simmons, A., Arridge, S. R., Tofts, P. S. and Barker, G. J. (1998) Application of the extremum stack to neurological MRI. IEEE Transactions on Medical Imaging, 17 (3). pp. 371-82. ISSN 0278-0062Full text not available from this repository.
The extremum stack, as proposed by Koenderink, is a multiresolution image description and segmentation scheme which examines intensity extrema (minima and maxima) as they move and merge through a series of progressively isotropically diffused images known as scale space. Such a data-driven approach is attractive because it is claimed to be a generally applicable and natural method of image segmentation. The performance of the extremum stack is evaluated here using the case of neurological magnetic resonance imaging data as a specific example, and means of improving its performance proposed. It is confirmed experimentally that the extremum stack has the desirable property of being shift-, scale-, and rotation-invariant, and produces natural results for many compact regions of anatomy. It handles elongated objects poorly, however, and subsections of regions may merge prematurely before each region is represented as a single node. It is shown that this premature merging can often be avoided by the application of either a variable conductance-diffusing preprocessing step, or more effectively, the use of an adaptive variable conductance diffusion method within the extremum stack itself in place of the isotropic Gaussian diffusion proposed by Koenderink.
|Keywords:||Brain/ anatomy & histology Humans Image Processing, Computer-Assisted/ methods Magnetic Resonance Imaging/ methods|
|Schools and Departments:||Brighton and Sussex Medical School > Brighton and Sussex Medical School|
|Depositing User:||Paul Stephen Tofts|
|Date Deposited:||14 Mar 2007|
|Last Modified:||30 Nov 2012 16:50|
|Google Scholar:||16 Citations|