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Homogeneity region based fuzzy-C means for breast cancer diagnosis

Othman, Khairulnizam and Ahmad , Afandi Homogeneity region based fuzzy-C means for breast cancer diagnosis. In: National Conference On Electrical And Electronic Engineering, 8-9 May 2012 , Batu Pahat, Johor, Malaysia.

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Abstract

Breast cancer has been one of leading causes of death among women since the last decades. The use of advanced high performance image processing methodologies will be usell in aiding clinicians in diagnosis and treatment planning. However, digital image fiom Breast Mammograms are diicult to process and this prompted the introduction of several novel image enhancement and clustering to improve digital mammography diagnosis. Here, we will, critically examine existing image preprocessing data structures used in association architecture rule for enhancing performance in attempt to understand their strength and weaknesses. Our analysis culminate in practical structured call BresCan-C (Breast Cancer Cluster) using different architecture where combine two clustering method to accompany it for the high accuracy diagnosis of processing. Experiments involving a wide range of breast mammogram database sets reveal that combination Homogeneity Region Based and Fuzzy-C means clustering create best architecture which gives excellent performance, analysis different sample also verifying its efficiency and viability.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: breast cancer; image enhancement; architecture; homogeneity region based; fuzzy-C means clustering
Subjects: T Technology > T Technology (General)
Depositing User: Normajihan Abd. Rahman
Date Deposited: 13 Aug 2018 03:41
Last Modified: 13 Aug 2018 03:41
URI: http://eprints.uthm.edu.my/id/eprint/7938
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