A new method based on texture analysis for the classification of automatic detection of breast microcalcifications of mammography images
Subject Areas : Biomedical Engineering
Zahra Maghsoodzadeh Sarvestani
1
(
Department of Electrical Engineering, Kazerun Branch, Islamic Azad University, Kazerun, Iran
)
Jasem Jamali
2
(
Department of Electrical Engineering, Kazerun Branch, Islamic Azad University, Kazerun, Iran
)
mhdi taghizadeh
3
(
Department of electrical and computer engineering, kazerun branch, islamic azad university, kazerun, iran
)
Mohammad h Fatehi
4
(
Department of Electrical Engineering, Kazerun branch, Islamic Azad University
)
Keywords: Texture analysis, fuzzy logic, Gabor filtering, artificial neural network (ANN), decision tree classification,
Abstract :
Mammography is a diagnostic technology used in screening programs to find breast cancer early. By using two techniques for image enhancement and highlighting breast tissue microcalcifications for the desired areas by regional ROI based on fuzzy system and also Gabor filtering method, the study's objective was to assess the viability of automatic separation of images of breast tissue microcalcifications and to assess its accuracy. The decision tree classification algorithm is used to categorize the clusters of breast tissue microcalcifications after the clusters have been identified. The samples that are thought to have microcalcification are next highlighted and masked for segmentation, and in the last step, tissue properties are extracted. Then, it was possible to distinguish between benign and malignant forms of segmented ROI clusters with the aid of an artificial neural network (ANN). The results of this work show a high accuracy of 93% and an improvement of sensitivity of 95%, which shows that the presented solution can be reliably applied to detect breast cancer..
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