Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Segmentation of medical images using a genetic algorithm
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Evolutionary approach to inverse planning in coplanar radiotherapy
Image and Vision Computing
Medical image segmentation using genetic algorithms
IEEE Transactions on Information Technology in Biomedicine
ICIC'07 Proceedings of the intelligent computing 3rd international conference on Advanced intelligent computing theories and applications
Automatic segmentation of bladder and prostate using coupled 3D deformable models
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention - Volume Part I
ICIC'10 Proceedings of the Advanced intelligent computing theories and applications, and 6th international conference on Intelligent computing
A genetic algorithm for color image segmentation
EvoApplications'13 Proceedings of the 16th European conference on Applications of Evolutionary Computation
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Segmentation of target organs and organs at risk is a fundamental task in radiotherapy treatment planning. Since its completion carried out by a radiation oncologist is really time-consuming, there is the need to perform it automatically. Unfortunately there is not a universal method capable to segment accurately every anatomical structure in every medical image, so each problem requires a study and an own solution. In this paper we analyze the problem of segmentation of bladder, prostate and rectum in lower abdomen CT images and propose a novel algorithm to solve it. It builds a statistical model of the organs analyzing a training set, generates potential solutions and chooses the segmentation result evaluating them on the basis of an aprioristic knowledge and the characteristics of patient image, using Genetic Algorithms. Out method has been tested qualitatively and quantitatively and offered good performance.