Title :
Classification of ductal tree structures in galactograms
Author :
Skoura, Angeliki ; Barnathan, Michael ; Megalooikonomou, Vasileios
Author_Institution :
Comput. Eng. & Inf. Dept., Univ. of Patras, Patras, Greece
fDate :
June 28 2009-July 1 2009
Abstract :
The objective of this study is the classification of galactograms, medical images which depict the ductal tree of human breast, in order to provide insight into the relationship between tree topology and radiological findings regarding breast cancer. We present two different descriptors for the classification of the ductal trees; the tree asymmetry index and the maximum common skeleton, both of which quantify the similarity between tree topologies. Experimental results demonstrate the effectiveness of the proposed approach, which reaches a classification accuracy of 83%, and also indicate that our method can potentially aid in early breast cancer diagnosis.
Keywords :
cancer; diagnostic radiography; image classification; medical image processing; X-ray galactogram; breast cancer; ductal tree structures; image classification; maximum common skeleton; radiology; tree asymmetry index; tree topology; Biomedical imaging; Breast; Cancer; Classification tree analysis; Dairy products; Data engineering; Ducts; Humans; Medical diagnostic imaging; Tree data structures; Cancer; Image classification; Magnetic resonance imaging; Trees;
Conference_Titel :
Biomedical Imaging: From Nano to Macro, 2009. ISBI '09. IEEE International Symposium on
Conference_Location :
Boston, MA
Print_ISBN :
978-1-4244-3931-7
Electronic_ISBN :
1945-7928
DOI :
10.1109/ISBI.2009.5193227