Breast Cancer Classification in Ultrasound Images using Transfer Learning -Deep Learning project-Matlab

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Breast Cancer Classification in Ultrasound Images using Transfer Learning -Deep Learning project-Matlab

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SKU: Breast Cancer Classification in Ultrasound Images Category:

Description

Breast Cancer Classification in Ultrasound Images using Transfer Learning -Deep Learning project-Matlab

Computer-aided detection of malignant breast tumors in ultrasound images has been receiving growing attention.

In this deep learning project , we propose a deep learning methodology to tackle this problem. The training data, which contains several hundred images of benign and malignant cases, was used to train a deep convolutional neural network (CNN).

Three training approaches are proposed: a baseline approach where the CNN architecture is trained from scratch, a transfer-learning approach where the pre-trained VGG16 CNN architecture is further trained with the ultrasound images, and a fine-tuned learning approach where the deep learning parameters are fine-tuned to overcome overfitting.

The experimental results demonstrate that the fine-tuned model had the best performance (0.97 accuracy, 0.98 AUC), with pre-training on US images. Creating pre-trained models using medical imaging data would certainly improve deep learning outcomes in biomedical applications.

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