An evolutionary algorithm for the segmentation of muscles and bones of the lower limb. (April 2016)

• Record Type: Journal Article
• Authors: Lpez, Marco A.; Braidot, A.; Sattler, Anbal; Schira, Claudia; Uriburu, E.
• Is Part Of: Journal of physics. Volume 705(2016)
• Publication Date: 2016-04
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/705/1/012021
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: In the field of medical image segmentation, muscles segmentation is a problem that has not been fully resolved yet. This is due to the fact that the basic assumption of image segmentation, which asserts that a visual distinction should ex- ist between the different structures to be identified, is infringed. As the tissue composition of two different muscles is the same, it becomes extremely difficult to distinguish one another if they are near. We have developed an evolutionary algorithm which selects the set and the sequence of morphological operators that better segments muscles and bones from an MRI image. The achieved results shows that the developed algorithm presents average sensitivity values close to 75% in the segmentation of the different processed muscles and bones. It also presents average specificity values close to 93% for the same structures. Furthermore, the algorithm can identify muscles that are closely located through the path from their origin point to their insertions, with very low error values (below 7%) .