Skull removal in MR images using a modified artificial bee colony optimization algorithm
- Resource Type
- Authors
- Mohammad Taherdangkoo
- Source
- Technology and Health Care. 22:775-784
- Subject
- Artificial bee colony optimization
Ant colony optimization algorithms
Skull
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Biomedical Engineering
Biophysics
Particle swarm optimization
Initialization
Health Informatics
Bioengineering
Biology
Magnetic Resonance Imaging
Biomaterials
medicine.anatomical_structure
Image Processing, Computer-Assisted
medicine
Humans
Preprocessor
Segmentation
Mr images
Algorithm
Algorithms
Information Systems
- Language
- ISSN
- 1878-7401
0928-7329
Removal of the skull from brain Magnetic Resonance (MR) images is an important preprocessing step required for other image analysis techniques such as brain tissue segmentation. In this paper, we propose a new algorithm based on the Artificial Bee Colony (ABC) optimization algorithm to remove the skull region from brain MR images. We modify the ABC algorithm using a different strategy for initializing the coordinates of scout bees and their direction of search. Moreover, we impose an additional constraint to the ABC algorithm to avoid the creation of discontinuous regions. We found that our algorithm successfully removed all bony skull from a sample of de-identified MR brain images acquired from different model scanners. The obtained results of the proposed algorithm compared with those of previously introduced well known optimization algorithms such as Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) demonstrate the superior results and computational performance of our algorithm, suggesting its potential for clinical applications.