Title :
Detection of Mammograms Using Honey Bees Mating Optimization Algorithm (M-HBMO)
Author :
Durgadevi, R. ; Hemalatha, B. ; Kaliappan, K. Vishnu Kumar
Author_Institution :
Dept. of Comput. Sci. & Eng., Jansons Inst. of Technol., Coimbatore, India
fDate :
Feb. 27 2014-March 1 2014
Abstract :
Mammography is the best available technique used by radiologists for screening early detection of breast cancer. In digital mammography the crisis of finding efficient and precise breast profile segmentation technique is time-consuming. In this research work, a novel hybrid method named M-HBMO (Mammogram based Honey Bees Mating Optimization) algorithm has been proposed to segment the lesion. The cancer profile segmentation is based on texture feature and extraction of the lesion. The M-HBMO is evaluated with conventional ROI (region of interest) Algorithm. The experiment is conducted with MRI images retrieved from the medical hospital database. The result proves that the M-HBMO method segments the breast region accurately correspond to respective MRI images.
Keywords :
biological tissues; cancer; diagnostic radiography; feature extraction; image segmentation; image texture; mammography; medical image processing; optimisation; M-HBMO; MRI image; ROI algorithm; breast cancer early detection; breast profile segmentation technique; breast region; cancer profile segmentation; digital mammography; hybrid method; lesion extraction; lesion segmentation; mammogram based honey bees mating optimization algorithm; mammogram detection; medical hospital database; radiology; region of interest algorithm; texture feature; Breast cancer; Image segmentation; Magnetic resonance imaging; Noise; Wiener filters; Filter; HBMO; Mammograms; ROI; Segmentation;
Conference_Titel :
Computing and Communication Technologies (WCCCT), 2014 World Congress on
Conference_Location :
Trichirappalli
Print_ISBN :
978-1-4799-2876-7
DOI :
10.1109/WCCCT.2014.52