Applying a new feature fusion method to classify breast lesions

Najmeh Mashhadi; Abolfazl Zargari Khuzani; Morteza Heidari; Donya Khaledyan; Sam Teymoori

doi:10.1117/12.2582753

15 February 2021 Applying a new feature fusion method to classify breast lesions

Najmeh Mashhadi, Abolfazl Zargari Khuzani, Morteza Heidari, Donya Khaledyan, Sam Teymoori

Proceedings Volume 11597, Medical Imaging 2021: Computer-Aided Diagnosis; 1159711 (2021) https://doi.org/10.1117/12.2582753
Event: SPIE Medical Imaging, 2021, Online Only

Abstract

Developing a computer-aided diagnosis (CAD) scheme to classify between malignant and benign breast lesions can play an important role in improving MRI screening efficacy. This study demonstrates that extracting features from both spatial and frequency domains, and applying an efficient combination of data reduction and classifier methods, had the potential to significantly improve accuracy in classifying between malignant and benign breast masses. By applying our CAD scheme to the testing dataset, we obtained an accuracy of 83.1% for the best combination of data reduction and classification (DNE-SVM).

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Citation Download Citation

Najmeh Mashhadi, Abolfazl Zargari Khuzani, Morteza Heidari, Donya Khaledyan, and Sam Teymoori "Applying a new feature fusion method to classify breast lesions", Proc. SPIE 11597, Medical Imaging 2021: Computer-Aided Diagnosis, 1159711 (15 February 2021); https://doi.org/10.1117/12.2582753

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