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SEDE
2008
15 years 1 months ago
Improving Fuzzy Algorithms for Automatic Magnetic Resonance Image Segmentation
: In this paper, we present reliable algorithms for fuzzy k-means and C-means that could improve MRI segmentation. Since the k-means or FCM method aims to minimize the sum of squar...
Ennumeri A. Zanaty, Sultan Aljahdali, Narayan C. D...
ITCC
2005
IEEE
15 years 5 months ago
Mining Biomedical Images with Density-Based Clustering
Density-based clustering algorithms have recently gained popularity in the data mining field due to their ability to discover arbitrary shaped clusters while preserving spatial pr...
M. Emre Celebi, Y. Alp Aslandogan, Paul R. Bergstr...
TIP
2008
125views more  TIP 2008»
14 years 11 months ago
Segmentation by Fusion of Histogram-Based K-Means Clusters in Different Color Spaces
Abstract--This paper presents a new, simple, and efficient segmentation approach, based on a fusion procedure which aims at combining several segmentation maps associated to simple...
Max Mignotte
ECCV
1998
Springer
16 years 1 months ago
Perceptual Smoothing and Segmentation of Colour Textures
An approach for perceptual segmentation of colour image textures is described. A multiscale representation of the texture image, generated by a multiband smoothing algorithm based ...
Maria Petrou, Majid Mirmehdi, M. Coors
TMI
2002
248views more  TMI 2002»
14 years 11 months ago
Adaptive Elastic Segmentation of Brain MRI via Shape Model Guided Evolutionary Programming
This paper presents a fully automated segmentation method for medical images. The goal is to localize and parameterize a variety of types of structure in these images for subsequen...
Alain Pitiot, Arthur W. Toga, Paul M. Thompson