Citation

Ting, F F and Sim, K S and Chong, S S (2017) Auto-probing breast cancer mass segmentation for early detection. In: 2017 International Conference on Robotics, Automation and Sciences (ICORAS), 27-29 Nov. 2017, Melaka, Malaysia.

Text 58.pdf - Published Version Restricted to Repository staff only Download (623kB)

Abstract

In this paper, an auto-probing breast cancer mass segmentation (ABC-MS) is proposed to assist medical doctors in breast cancer diagnosis. Manual segmentation is implemented as standard diagnosis procedure for medical doctors. This algorithm can detect and segment the breast cancer abnormality without prior knowledge regarding its presence. Automated single seed point region growing is utilised in this algorithm to perform the mass detection and segmentation automatically. Comparison with commercial semi-automated segmentation application is performed. Tabulated experiment results showed the proposed method outperformed the compared method by having accuracy at 90% and area under curve (AUC) at 0.895 ± 0.0338

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Image processing
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) > TA1501-1820 Applied optics. Photonics
Divisions:	Faculty of Engineering and Technology (FET)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	24 Apr 2021 14:41
Last Modified:	24 Apr 2021 14:41
URII:	http://shdl.mmu.edu.my/id/eprint/7638

Downloads

Edit (login required)