Ultrasonic Image Processing for the Classification of Benign and Malignant Breast Tumors: Comparative Study of Convolutional Neural Network Architectures

Ultrasonic Image Processing for the Classification of Benign and Malignant Breast Tumors: Comparative Study of Convolutional Neural Network Architectures

This study addresses the limitations of conventional breast cancer diagnosis using ultrasound imaging and machine learning. Using KAGGLE data, we applied preprocessing techniques to identify tumour features. VGGNET16 demonstrated 90% accuracy, simplifying tumour classification. Our findings highligh...

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Bibliographic Details
Main Authors: Erick Acuña Chambi, Daniel Gil Alzamora, Antonio Angulo Salas
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Engineering Proceedings
Subjects:
cancer
breast
imaging
ultrasound
CNN
benign
Online Access:https://www.mdpi.com/2673-4591/83/1/15
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