Use of Transfer Learning and Wavelet Transform for Breast Cancer Detection

• URL: http://arxiv.org/abs/2103.03602v1
• Date: Fri, 5 Mar 2021 11:08:56 GMT
• Title: Use of Transfer Learning and Wavelet Transform for Breast Cancer Detection
• Authors: Ahmed Rasheed, Muhammad Shahzad Younis, Junaid Qadir and Muhammad Bilal
• Abstract summary: Deep learning is widely used for the detection of cancerous masses in the images obtained via mammography. We introduce segmentation and wavelet transform to enhance the important features in the image scans. Our proposed system aids the radiologist in the screening phase of cancer detection by using a combination of segmentation and wavelet transforms.
• Score: 6.14950556643824
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Breast cancer is one of the most common cause of deaths among women. Mammography is a widely used imaging modality that can be used for cancer detection in its early stages. Deep learning is widely used for the detection of cancerous masses in the images obtained via mammography. The need to improve accuracy remains constant due to the sensitive nature of the datasets so we introduce segmentation and wavelet transform to enhance the important features in the image scans. Our proposed system aids the radiologist in the screening phase of cancer detection by using a combination of segmentation and wavelet transforms as pre-processing augmentation that leads to transfer learning in neural networks. The proposed system with these pre-processing techniques significantly increases the accuracy of detection on Mini-MIAS.

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