Channeler Ant Model: 3D segmentation of medical images through ant colonies

Fiorina, E. and Arteche Diaz, R. and Bosco, P. and Gargano, G. and Massafra, A. and Megna, R. and Oppedisano, C. and Valzano, S. (2011) Channeler Ant Model: 3D segmentation of medical images through ant colonies. Il nuovo cimento C, 34 (1). pp. 79-89. ISSN 1826-9885

ncc9756.pdf - Published Version

Download (464kB) | Preview
Official URL:


In this paper the Channeler Ant Model (CAM) and some results of its applications to the analysis of medical images are described. The CAM is an algorithm able to segment 3D structures with different shapes, intensity and background. It makes use of virtual ant colonies and exploits their natural capabilities to modify the environment and communicate with each other by pheromone deposition. Its performance has been validated with the segmentation of 3D artificial objects and it has been already used successfully in lung nodules detection on Computer Tomography images. This work tries to evaluate the CAM as a candidate to solve the quantitative segmentation problem in Magnetic Resonance brain images: to evaluate the percentage of white matter, gray matter and cerebrospinal fluid in each voxel.

Item Type: Article
Uncontrolled Keywords: Neural networks, fuzzy logic, artificial intelligence ; Computer-aided diagnosis ; Medical imaging ; Computed tomography
Subjects: 500 Scienze naturali e Matematica > 530 Fisica
Depositing User: Marina Spanti
Date Deposited: 03 Apr 2020 15:13
Last Modified: 03 Apr 2020 15:13

Actions (login required)

View Item View Item