maximize


@inproceedings{DrMeRuSc01,
  author = {Droske, M. and Meyer, B. and Rumpf, M. and Schaller, C.},
  title = {An adaptive level set method for medical image segmentation},
  booktitle = {Annual Symposium on Information Processing in Medical Imaging},
  year = {2001},
  editor = {R. Leahy and M. Insana},
  publisher = {Springer, Lecture Notes Computer Science},
  abstract = {An efficient adaptive multigrid level set method for front propagation
	purposes in three dimensional medical image processing and segmentation
	is presented. It is able to deal with non sharp segment boundaries.
	A flexible, interactive modulation of the front speed depending on
	various boundary and regularization criteria ensure this goal. Efficiency
	is due to a graded underlying mesh implicitly defined via error or
	feature indicating values on the cells of the underlying hexahedral
	grid. A suitable saturation condition ensures an important regularity
	condition on the resulting adaptive grid. This simplifies the adaptive
	fast marching method on the compressed data significantly. As an
	application the segmentation of glioma is considered. Thus the clinician
	interactively selects a few parameters describing the speed function
	and a few seed points referring to a single slice of an MRI data
	set. Then the automatic process of front propagation generates a
	family of segments corresponding to the evolution of the front in
	time, from which the clinician finally selects an appropriate segment
	covered by the gliom. This selection can be based on a visual evaluation
	of the propagation on a reference slice using the clinicians expert
	knowledge. Thus, the overall glioma segmentation turns into an efficient,
	nearly real time process with intuitive and usefully restricted user
	interaction.},
  pdf = {http://numod.ins.uni-bonn.de/research/papers/public/DrMeRuSc01.pdf 1}
}