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Application of Wavelet de-noising Filters in Mammogram Images Classification Using Fuzzy Soft Set

Anwar Lashari, Saima and Ibrahim, Rosziati and Senan, Norhalina and Tri Riyadi Yanto, Iwan and Herawan, Tutut (2018) Application of Wavelet de-noising Filters in Mammogram Images Classification Using Fuzzy Soft Set. [Artikel Dosen]

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Abstract

Recent advances in the field of image processing have revealed that the level of noise in mammogram images highly affect the images quality and classification performance of the classifiers. Whilst, numerous data mining techniques have been developed to achieve high efficiency and effectiveness for computer aided diagnosis systems. However, fuzzy soft set theory has been merely experimented for medical images. Thus, this study proposed a classifier based on fuzzy soft set with embedding wavelet de-noising filters. Therefore, the proposed methodology involved five steps namely: MIAS dataset, wavelet de-noising filters hard and soft threshold, region of interest identification, feature extraction and classification. Therefore, the feasibility of fuzzy soft set for classification of mammograms images has been scrutinized. Experimental results show that proposed classifier FussCyier provides the classification performance with Daub3 (Level 1) with accuracy 75.64% (hard threshold), precision 46.11%, recall 84.67%, F-Micro 60%. Thus, the results provide an alternative technique to categorize mammogram images. Keywords: Mammogram images; Feature extraction; Wavelet filters; Fuzzy soft set.

Item Type: Artikel Dosen
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisi / Prodi: Faculty of Mathematics and Natural Sciences (Fakultas Matematika dan Ilmu Pengetahuan Alam) > S1-Information System (S1-Sistem Informasi)
Depositing User: Iwan Tri Riyadi Yanto
Date Deposited: 06 Nov 2018 06:59
Last Modified: 06 Nov 2018 06:59
URI: http://eprints.uad.ac.id/id/eprint/11619

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