MRT letter: segmentation and texture-based classification of breast mammogram images.

Abstract:

:Breast cancer is the most common cancer diagnosed among women. In this article, support vector machine is used to classify digital mammogram images into malignant and benign. Wiener filter is used to handle the possible quantum noise, which is more likely to occur in mammograms. Stack-based connected component method is proposed for background removal, and the image is enhanced using retinax method. Seeded region growing algorithm is used to remove the pectoral muscle part of the mammogram. We have extracted 13 different multidomains' features for classification. Results show the superiority of the proposed algorithm in terms of sensitivity, specificity, and accuracy. We have used MIAS database of mammography for experimentation.

journal_name

Microsc Res Tech

authors

Naveed N,Jaffar MA,Choi TS

doi

10.1002/jemt.21070

subject

Has Abstract

pub_date

2011-11-01 00:00:00

pages

985-7

issue

11

eissn

1059-910X

issn

1097-0029

journal_volume

74

pub_type

信件
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    authors: Cyr DG,Robaire B,Hermo L

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    doi:10.1002/1097-0029(20010101)52:1<65::AID-JEMT9>3.0.

    authors: Chodobski A,Szmydynger-Chodobska J

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    doi:10.1002/jemt.1070310404

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    更新日期:2017-02-01 00:00:00

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    authors: Vanthanouvong V,Kozlova I,Roomans GM

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    doi:10.1002/jemt.22534

    authors: Novaes RD,Sequetto PL,Vilela Gonçalves R,Cupertino MC,Santos EC,Mello VJ,Araújo MR,Silva E,Oliveira TT

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    authors: Himmelhoch S

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    abstract::Sequences highly similar (>95%) to the mouse mammary tumor virus (MMTV) env gene have been amplified from human DNA samples, including DNA samples from patients with breast cancer (BC) and persons who did not have BC. The sequences from human DNA were distinct from the MMTV sequences used as controls in these PCR reac...

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  • Apoptosis of larval cells during amphibian metamorphosis.

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    authors: Ishizuya-Oka A

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