Title :
A hybrid system for detecting masses in mammographic images
Author :
Székely, Nora ; Tóth, Norbert ; Pataki, Béla
Author_Institution :
Dept. of Meas. & Inf. Syst., Budapest Univ. of Technol. & Econ., Hungary
Abstract :
This paper discusses a hybrid system for detecting masses in mammographic images. The proposed approach analyses the mammograms in three major steps. First a global segmentation method is applied to find the regions of interest. This step uses texture features, decision trees and a multiresolution Markov random field model. The second stage works on the output of the previous algorithm. Here a combination of three different local segmentation methods is used, and then some relevant features are extracted. Some of them refer to the shape of the object, others are simple texture parameters. Based on these features the final decision is made.
Keywords :
Markov processes; decision trees; feature extraction; image segmentation; image texture; mammography; medical image processing; principal component analysis; decision trees; feature extraction; global segmentation method; hybrid system; local segmentation methods; mammographic images; masses detection; multiresolution Markov random field model; regions of interest; texture features; Biomedical imaging; Biomedical measurements; Breast cancer; Cancer detection; Image analysis; Image segmentation; Information systems; Lesions; Mammography; Shape;
Conference_Titel :
Instrumentation and Measurement Technology Conference, 2004. IMTC 04. Proceedings of the 21st IEEE
Print_ISBN :
0-7803-8248-X
DOI :
10.1109/IMTC.2004.1351496