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Detection of masses and microcalcifications in digital mammogram images using fuzzy logic Cover

Detection of masses and microcalcifications in digital mammogram images using fuzzy logic

Open Access
|Jan 2017

Figures & Tables

Figure 1

A: Selected region on i535, B: Selected region on i541
A: Selected region on i535, B: Selected region on i541

Figure 2

ROC curve of the suggested system diagnosis and diagnosis by the 3 radiologists. Diagonal segments are produced by ties.
ROC curve of the suggested system diagnosis and diagnosis by the 3 radiologists. Diagonal segments are produced by ties.

The accuracy of suggested method against trae diagnosis

True diagnosisTotal
AbnormalNormal
Suggested Method
Abnormal11318131
Normal19176195
Total132194326

Sensitivity and specificity of radiologists and suggested method (Mammographic Image Analysis Society database images)

Sensitivity (%)Specificity (%)
Suggested system85.690.7
R187.994.3
R284.990.7
R378.088.7

The accuracy of the radiologists against true diagnosis

True diagnosisTotal
AbnormalNormal
R1Abnormal11611127
Normal16183199
Total132194326
R2Abnormal11218130
Normal20176196
Total132194326
R3Abnormal10322125
Normal29172201
Total132194326
DOI: https://doi.org/10.5372/1905-7415.1004.497 | Journal eISSN: 1875-855X | Journal ISSN: 1905-7415
Language: English
Page range: 345 - 350
Published on: Jan 31, 2017
Published by: Chulalongkorn University
In partnership with: Paradigm Publishing Services
Publication frequency: 6 issues per year

© 2017 Mostafa Langarizadeh, Rozi Mahmud, Rafat Bagherzadeh, published by Chulalongkorn University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.