Paper Info
Title
Liver Segmentation Using Level Sets And Genetic Algorithms
Abstract
This paper presents a method based on level sets to segment the liver using Computer Tomography (CT) images. Initially, the liver boundary is manually set in one slice as an initial solution, and then the method automatically segments the liver in all other slices, sequentially. In each step of iteration it fits a Gaussian curve to the liver histogram to model the speed image in which the level sets propagates. The parameters of our method were estimated using Genetic Algorithms (GA) and a database of reference segmentations. The method was tested using 20 different exams and five different measures of performance, and the results obtained confirm the potential of the method. The cases in which the method presented a poor performance are also discussed in order to instigate further research.
Year
Venue
Keywords
2009
VISAPP 2009: PROCEEDINGS OF THE FOURTH INTERNATIONAL CONFERENCE ON COMPUTER VISION THEORY AND APPLICATIONS, VOL 2
Medical Imaging, Liver Segmentation, Computer Tomography, Level Sets, Genetic Algorithms
Field
DocType
Citations 
Computer vision,Histogram,Pattern recognition,Computer science,Segmentation,Level set,Tomography,Artificial intelligence,Quality control and genetic algorithms,Gaussian function,Genetic algorithm
Conference
1
PageRank 
References 
Authors
0.36
3
3
Name
Order
Citations
PageRank
Dário Augusto B. Oliveira1236.45
Raul Feitosa28619.13
Mauro M. Correia310.36