Development of Deep Learning Based Self Examination of Breast Cancer

Development of Deep Learning Based Self Examination of Breast Cancer

 

 

Dr. Sumitha C

Professor, Dept. of EEE.

G Madegowda Institute of Technology Bharathinagara, Mandya,

India

sumithac.gmiteee@gmail.com

Dr. Nuthan A C

Professor, Dept. of ECE.

G Madegowda Institute of Technology Bharathinagara, Mandya,

India

nuthanac.gmitece@gmail.com

Kavyashree H N

Student, Dept. of EEE. G Madegowda Institute of

Technology Bharathinagara, Mandya,

India

kavyashree1209@gmail.com

Srushti M P

Student, Dept. of EEE. G Madegowda Institute of

Technology Bharathinagara, Mandya,

India

srushtimp2003@gmail.com

Thanushree N Gowda

Student, Dept. of EEE. G Madegowda Institute of

Technology Bharathinagara, Mandya,

India

thanugowda1508@gmail.com

Vandana M C

Student, Dept. of EEE. G Madegowda Institute of

Technology Bharathinagara, Mandya, India

vandanamc14@gmail.com

 

 

 

Abstract - The Breast cancer is one of the leading causes of death among women worldwide. Early detection significantly increases the chances of successful treatment. However, in many regions, access to diagnostic tools and medical professionals is limited. This paper presents a deep learning- based system designed to aid in the self-examination of breast cancer using smartphone-acquired photographic images. The acquired images are encrypted using the RSA algorithm to ensure privacy. The proposed system utilizes convolutional neural networks (CNNs), specifically employing a Decision Tree Classifier, to predict the likelihood of cancer based on user-provided images. The model supports multilingual capabilities to cater to non-technical users. Experimental results show promising accuracy, suggesting that deep learning can support accessible and affordable early detection methods.

Keywords - Breast Cancer, Deep Learning, CNN, Self Examination, Medical Imaging, Image Classification.