Robust Retrieval of 3D Structures from Image Stacks
Maria Garza-Jinich(1), Peter Meer(2) and Veronica Medina(3)
(1)Departamento de Ingenieria Electrica
Instituto de Investigaciones en Matematicas Aplicadas y en Sistemas
Universidad Nacional Autonoma de Mexico, Mexico D.F. 01000.
(2)Department of Electrical and Computer Engineering
Rutgers University, Piscataway, NJ 08855, USA.
(3)Departamento de Ingenieria Electrica
Universidad Autonoma Metropolitana, Iztapalapa, Mexico D.F. 09340.
Robust high breakdown point location estimators are
employed to analyze image stacks under the piecewise constant
image structure model. To reduce the effect of bias along the Z axis,
the class parameters are extracted using three consecutive slices.
The segmentation algorithm first determines the most reliable seed
regions which are then
used in a region-growing procedure supported by local evidence.
The robustness and stability of the proposed technique is shown
with both synthetic and real data, the latter consisting of one
MRI and one confocal microscopy set.
The performance of the algorithm is consistent with the
ground truth obtained with manual segmentation by physicians.
Medical Image Analysis, vol. 3, 21-35, 1999.
A shorter version appeared as,
M. Garza-Jinich, P. Meer, V. Medina:
Robust retrieval of 3D structures
from magnetic resonance images.
13th International Conference on
Pattern Recognition: Pattern Recognition and Signal Analysis.
C: Applications and Robotics Systems.
Vienna, Austria, August 1996, 391-395.
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